Urbanization and Sustainable Land Use Planning 
Challenges in the Mazandaran Metropolitan Area,  
the Case of Sari City 
A Dissertation Submitted to the Faculty of Spatial Planning 
at Technical University of Dortmund 
In accordance with the requirements for the degree of Doctor of Engineering 
(Dr.-Ing.) 
 
by 
Ahmad Sahraei Juybari 
 
Supervisor: 
Frau Prof. Dipl.-Ing. Christa Reicher, “Chair of Urban Design and Institute for 
Urban Design and European Urbanism”, Faculty of Architecture,  
RWTH Aachen University 
Supervisor: 
Herr Prof. Dr.-Ing. Frank Othengrafen, “Chair of Urban and Regional 
Planning”, Faculty of Spatial Planning, Technical University of Dortmund 
Chairperson: 
Frau Prof. Dr. Sophie Schramm, “Chair of International Planning Studies (IPS)”, 
Faculty of Spatial Planning, Technical University of Dortmund 
 
Dortmund, Germany 
February 2023
 
 
 
 
 
Dissertation, Fakultät Raumplanung, TU Dortmund, Dortmund. 
Dissertation, Faculty of Spatial Planning, TU Dortmund, Dortmund. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
II 
 
 
Doctoral Committee 
 
First Supervisor: 
Frau Prof. Dipl.-Ing. Christa Reicher, “Chair of 
Urban Design and Institute for Urban Design and 
European Urbanism”, Faculty of Architecture, 
RWTH Aachen University 
  
Second Supervisor: 
Herr Prof. Dr.-Ing. Frank Othengrafen, 
“Chair of Urban and Regional Planning”, Faculty of 
Spatial Planning, Technical University of Dortmund 
 
 
Chairperson: 
Frau Prof. Dr. Sophie Schramm, “Chair of 
International Planning Studies (IPS)”, Faculty of Spatial 
Planning, Technical University of Dortmund 
 
 
 
 
 
Date of Disputation: 18.08.2022 
III 
 
 
Declaration 
With this, the author declares that all information in this academic work (Ph.D. 
thesis) has been independently and originally written and completed to fulfill the 
requirement for a Doctor of Engineering (Dr.-Ing.) degree. Also, as required by these 
rules and conduct, the author has fully cited and referenced all materials and results 
that are not original to this work. 
Ahmad Sahraei Juybari 
February 2023 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
IV 
 
Abstract 
After the industrial revolution in the late eighteenth century, massive changes in the 
social and economic sectors occurred, particularly in cities. These changes have 
accelerated urban growth by providing more financial resources and opportunities for 
urban areas than rural areas. As a result, cities have become larger, more populated 
than rural areas, and urban issues have become more complex and serious. 
The city of Sari, since the last decades, has been facing massive migration, 
uncontrolled land-use change, non-sustainable consumption of farmlands, and 
sprawling growth. Simultaneously growing the city, the city's issues became more 
challenging. Methodologically, this thesis benefits from methodological pluralism and 
seeks to analyze the city of Sari with attention to the defined objectives and questions 
in chapter one. Methodological pluralism involves employing multiple methods to 
obtain a value. Therefore, this thesis applied several mathematical models and 
softwares considering the types of data. Parts of the data were collected from the 
published data and reports by Iran’s national and regional organizations. Moreover, 
some of the data that were not available were collected through field works, surveys, 
and interviews with experts and managers. The results show that the current 
centralized political structure has made urban management ineffective and reduced 
public participation in the planning and executing processes. The results of the models 
for analyzing the urban system in the Mazandaran metropolitan area have shown 
agglomeration of the population in the urban areas, especially in the big cities, 
particularly in Sari. The urban system is centralized, and there is an imbalance 
between the size and rank of cities, especially in big cities. Also, the results of land-
use change modeling and working with satellite images have shown that the city of 
Sari has been faced with massive sprawling growth, particularly during the last 
decades. And finally, the results of land-use changes analysis using GIS and aerial 
images have shown progressed unplanned land-use changes, particularly near the 
official border of Sari city. 
Keywords: Planning system; Urban development; Land use changes; Land 
consumption; Urban sprawl growth; The Mazandaran metropolitan area; Sari city 
V 
 
Acknowledgments 
It gives the author a great pleasure in expressing his most profound gratitude, 
especially to his supervisor, Prof. Dipl.-Ing. Christa Reicher, for her constant 
guidance, support, motivation, and untiring help. The author is very much obliged to 
her for her insightful comments and constructive criticisms at different stages. 
Also, the author is grateful to his other supervisor, Prof. Dr.-Ing. Frank 
Othengrafen, for his patience and detailed guidance and suggestions during the 
completion of this dissertation. 
The author also thanks Prof. Dr. Sophie Schramm for her support and acceptance 
as the chairperson of this dissertation. 
The following thanks goes to the Faculty of Spatial Planning, Dortmund Catholic 
Student Community, AStA TU Dortmund, Prof. Sigrun Dechêne, Mitra Haghnegad 
and her family, Eva-Maria Stein Hoffer, and Horst Wessel “chef of the Moskito GIS 
Company.” 
The author wants to extend his heartfelt respect and deep appreciation to his dear 
caring parents, his precious and lovely one Eva-Carolin aCampo (Superheldin) and 
her caring parents, his dear sister Mobina, and his dear brothers Mohammad and Ali 
for their love and tremendous support throughout the whole process. 
Also, this is a valuable opportunity for the author to thank all people who have 
supported him during his life to be in this stage of success, especially while writing 
this thesis. 
 
Ahmad Sahraei Juybari 
February 2023 
 
VI 
 
Table of Contents 
Chapter One .................................................................................................................................................... 1 
1.1. Introduction................................................................................................................................... 2 
1.2. The city of Sari ............................................................................................................................. 7 
1.3. Research questions ........................................................................................................................ 9 
1.3.1. The main question .................................................................................................................... 9 
1.3.2. The subsidiary questions.......................................................................................................... 9 
1.4. Research propositions ................................................................................................................... 9 
1.5. Research objectives..................................................................................................................... 10 
1.5.1. General objective ................................................................................................................... 10 
1.5.2. Specific objectives .................................................................................................................. 10 
1.6. Methodology ............................................................................................................................... 10 
1.6.1. Methods and tools for data collection ................................................................................... 10 
1.6.2. Data analysis ......................................................................................................................... 11 
1.7. Innovation ................................................................................................................................... 12 
1.8. Limitations .................................................................................................................................. 12 
1.8.1. Personal limitations ............................................................................................................... 12 
1.8.2. Research limitations .............................................................................................................. 12 
Chapter Two .................................................................................................................................................. 14 
2.1. Anthropogenic urbanization........................................................................................................ 15 
2.2. The major aspects of the contemporary urbanization ................................................................. 16 
2.2.1. The scale of urbanization....................................................................................................... 16 
2.2.2. The rate of urbanization ........................................................................................................ 17 
2.2.3. Urbanization and size of cities .............................................................................................. 18 
2.3. Drivers of urbanization ............................................................................................................... 20 
2.4. Cycles of urbanization and counterurbanization ......................................................................... 25 
2.5. Continental urbanization ............................................................................................................. 30 
2.5.1. Urbanization in Europa .................................................................................................................... 30 
2.5.2. Urbanization in North America ........................................................................................................ 30 
2.5.3. In the Latin American countries ....................................................................................................... 33 
.2.5.4 Urbanization in Africa ..................................................................................................................... 34 
2.5.5. Urbanization in Asia ........................................................................................................................ 36 
2.6. Sustainable urbanization ............................................................................................................. 37 
2.6.1. Toward a sustainable urbanized world ................................................................................. 37 
2.6.2. Urbanization and urban land use sustainability .................................................................... 39 
2.6.3. Urbanization and economic development .............................................................................. 40 
Chapter Three ............................................................................................................................................... 42 
3.1. Sustainable development ............................................................................................................ 43 
VII 
 
3.2. The emergence of sustainable development theory .................................................................... 43 
3.2.1. Stockholm conference  ........................................................................................................... 43 
3.2.2. Brundtland commission  ........................................................................................................ 44 
3.2.2.1. The main aspects of Brundtland’s report .................................................................................... 45 
3.2.2.2. The main dimensions of sustainable development in the Brundtland’s report ........................... 46 
3.2.2.2.1. The objectives of environmental sustainability: ......................................................................... 46 
3.2.2.2.2. The objectives of economic sustainability: ................................................................................ 46 
3.2.2.2.3. The objectives of social sustainability: ....................................................................................... 46 
3.2.2.2.4. The objectives of physical and political sustainability: .............................................................. 46 
3.2.3. Earth summit.......................................................................................................................... 47 
3.2.4. Johannesburg summit ............................................................................................................ 47 
3.3. Urban sustainability .................................................................................................................... 48 
Chapter Four ................................................................................................................................................. 49 
4.1. Urban growth .............................................................................................................................. 50 
4.2. Criteria of urban changes concerning the urban environment .................................................... 52 
4.3. Changing urban environment under social changes .................................................................... 55 
4.4. The consequence of population changes on land use changes .................................................... 59 
4.5. Social equality and land use sustainability ................................................................................. 60 
4.6. The characteristics of suburbans ................................................................................................. 62 
4.7. Urban sprawl growth .................................................................................................................. 64 
4.8. Urban density, efficiency and effectivity .................................................................................... 64 
4.9. Density and optimizing structure and size of cities .................................................................... 67 
4.10. Costs of sprawlization ................................................................................................................. 68 
4.10.1. Social costs ....................................................................................................................... 72 
4.10.2. Economic cots ................................................................................................................... 76 
4.11. Smart growth and counterurbanization ....................................................................................... 79 
4.12. Concept of urban smart growth................................................................................................... 81 
Chapter Five .................................................................................................................................................. 83 
5.1. Land ............................................................................................................................................ 84 
5.2. Land use ...................................................................................................................................... 85 
5.2.1. Time ....................................................................................................................................... 87 
5.2.2. Place and space ..................................................................................................................... 87 
5.3. Sustainable land use .................................................................................................................... 89 
5.4. Land management and land administration ................................................................................ 89 
5.4.1. Land ownership ..................................................................................................................... 91 
5.4.2. Land-use types ....................................................................................................................... 91 
5.4.3. Land use development............................................................................................................ 91 
5.5. Urban land-use planning ............................................................................................................. 92 
5.6. Complexity in the process of urban land use planning ............................................................... 93 
5.7. The land use classification .......................................................................................................... 95 
VIII 
 
Chapter Six .................................................................................................................................................... 97 
Methodology .................................................................................................................................................. 97 
6.1. The applied demographic projection models .............................................................................. 98 
6.1.1. Projection of population growth ............................................................................................ 98 
6.1.2. Modified exponential model .................................................................................................. 98 
6.1.3. Linear regression model ........................................................................................................ 99 
6.1.4. Elasticity analysis ................................................................................................................ 100 
6.2. The Rank-Size Rule and Zipf’s law .......................................................................................... 100 
6.3. Regression model ...................................................................................................................... 101 
6.4. Location Quotient model (L.Q) ................................................................................................ 102 
6.5. Entropy Index ........................................................................................................................... 103 
6.6. Isard's Longitudinal and Transverse model .............................................................................. 103 
6.7. Lorenz Curve ............................................................................................................................ 105 
6.8. The Gini coefficient .................................................................................................................. 105 
6.9. MAXLIKE (Maximum Likelihood) ......................................................................................... 106 
6.10. Land change modeler ................................................................................................................ 106 
6.10.1. The Change Prediction Process in LCM ........................................................................ 106 
6.10.2. Change analysis.............................................................................................................. 107 
6.10.3. Transition Potential Modeling ........................................................................................ 108 
6.10.4. Change prediction .......................................................................................................... 108 
6.10.5. Hard classifying.............................................................................................................. 109 
6.10.6. Soft classifying ................................................................................................................ 109 
6.11. Markov model ........................................................................................................................... 109 
6.12. Cellular utomaton Markov model ............................................................................................. 110 
Chapter Seven ............................................................................................................................................. 111 
7.1. Population ................................................................................................................................. 112 
7.2. Population growth rate .............................................................................................................. 113 
7.3. Elasticity analysis ..................................................................................................................... 122 
7.4. The projections of the population growth ................................................................................. 125 
7.4.1. The results of the projected population growth at the national level................................... 125 
7.4.2. The results of the projected population growth in the Mazandaran metropolitan area ...... 128 
7.4.3. The results of the projected population growth at the local level ........................................ 130 
Chapter Eight .............................................................................................................................................. 132 
8.1. The results of Rank-Size Rule, Zipf's law for the decade 1986 ................................................ 135 
8.2. The results of Regression model for the decade 1986 .............................................................. 137 
8.3. The results of Rank-Size Rule, Zipf's law for the decade 1996 ................................................ 140 
8.4. The results of Regression model for the decade 1996 .............................................................. 142 
8.5. The results of Rank-Size Rule, Zipf's law for the decade 2006 ................................................ 145 
IX 
 
8.6. The results of Regression model for the decade 2006 .............................................................. 147 
8.7. The Rank-Size Rule, Zipf's law for the decade 2016 ................................................................ 150 
8.8. The Regression model for the decade 2016 .............................................................................. 152 
8.9. The results of Location Quotient model (L.Q).......................................................................... 159 
8.10. The results of Isard's longitudinal and transverse model .......................................................... 167 
8.11. The results of Lorenz Curve and calculating Gini Coefficient ................................................. 177 
8.12. The results of Entropy Index..................................................................................................... 190 
Chapter Nine ............................................................................................................................................... 196 
9.1. Introduction............................................................................................................................... 197 
9.2. The big bang of Iran's cities ...................................................................................................... 200 
.9.3 Pervasiveness systemized and principled urbanization ............................................................. 223 
9.4. Analysis of the contents of urban development plans ............................................................... 247 
Chapter Ten ................................................................................................................................................. 250 
10.1. Introduction............................................................................................................................... 251 
10.2. Maximum Likelihood ............................................................................................................... 254 
10.3. The change prediction process in LCM .................................................................................... 255 
10.4. Transition potential modeling ................................................................................................... 256 
10.5. Hard classifying ........................................................................................................................ 257 
10.6. Soft classifying ......................................................................................................................... 257 
10.7. Markov model ........................................................................................................................... 257 
10.7.1. Cellular Automaton Markov Model ................................................................................ 258 
Chapter Eleven ............................................................................................................................................ 281 
11.2. The subdivided land parcels...................................................................................................... 287 
11.3. The subdivided and built-up parcels ......................................................................................... 287 
11.4. The subdivided and under construction parcels ........................................................................ 288 
11.5. The interactions among the factors including: time of development, urban density and area of 
land parcels   .................................................................................................................................................. 301 
11.6. Planned and unplanned land subdividing and zoning ............................................................... 303 
Chapter Twelve ........................................................................................................................................... 331 
12.1. Conclusions............................................................................................................................... 333 
12.2. Solutions ................................................................................................................................... 340 
References................................................................................................................................................ 349 
 
 
 
X 
 
Figures 
Figure 1 The geographical locations of counties and cities in the Mazandaran metropolitan area, (by the author) 3 
Figure 2 Classification of cities in the Mazandaran metropolitan area considering population (by the author) ..... 4 
Figure 3 Topography of the Mazandaran metropolitan area and location of cities (by the author) ........................ 5 
Figure 4 Conceptual model of this thesis (by the author) ....................................................................................... 6 
Figure 5 The main forces of land use change (by the author) ................................................................................. 7 
Figure 6 The geographical position of Sari county and Sari city (by the author) ................................................... 8 
Figure 7 Conceptual model of this Ph.D. thesis considering methodology and data analysis processing (by the 
author) ........................................................................................................................................................ 12 
Figure 8 The distribution of the world population (Cox, 2021) ............................................................................ 17 
Figure 9 The world’s urban population growth by region (Karen C. Seto, Roberto Sanchez-Rodrıguez, Michail 
Fragkias, 2010) ........................................................................................................................................... 18 
Figure 10 Number of people living in urban and rural areas globally , 1960 to 2020 (ourworldindata, 2021) .... 18 
Figure 11  Classification of the urban population considering size and number of cities globally, between1970 to 
2030 (United Nations, 2014). ..................................................................................................................... 19 
Figure 12 Conceptual model of migrations between places within space and time (by the author) ..................... 20 
Figure 13 Internal connections and interactions among elements in an one-dimensional space (by the author) .. 21 
Figure 14 In- External connections and interactions between spaces and elements in multiple dimensional spaces 
(by the author) ............................................................................................................................................ 22 
Figure 15 Urban and rural demographic changes over centuries (ourworldindata, 2021) .................................... 23 
Figure 16 Percentage of the global population living in urban areas from 1950 to 2050 (World Health 
Organization, 2018) .................................................................................................................................... 24 
Figure 17 Modelling the phases of urban development. Meaning of the abbreviations: – A, absolute; R, relative; 
C, centralization; D, decentralization (Paddison, 2001) ............................................................................. 26 
Figure 18 Temporal Characterization of Differential Urbanization (Hermanus S. Geyer, Thomas Kontuly, 1993).
 .................................................................................................................................................................... 28 
Figure 19 The conceptual model of the Phases of Differential Urbanization: Mainstream and Sub-stream 
Movements (Hermanus S. Geyer, Thomas Kontuly, 1993). ...................................................................... 29 
Figure 20 Pioneer mass-builder Fritz Burns developed Westchester in the late 1930s, devising many of the 
mass-production techniques adopted by postwar suburban builders through the United States (Becky 
Nicolaides, Andrew Wiese, 2017). ............................................................................................................. 31 
Figure 21 The population of urban areas in the United States, 1790-2021 (Leah Platt Boustan, Devin Bunten, 
Owen Hearey, 2013). ................................................................................................................................. 31 
Figure 22 U.S. urban rent premium, 1918-2010. It represents the premium nationally for households of 
industrial workers living in cities (Leah Platt Boustan, Devin Bunten, Owen Hearey, 2013). .................. 32 
Figure 23 Irvine, California, exemplified the massive scale of suburban developments after 1960 and their 
multiple functions including suburban housing, offices, retail, and industry. Irvine housed more than 
60,000 people by 1980 and 212,000 by 2010 (Becky Nicolaides, Andrew Wiese, 2017). ........................ 33 
Figure 24 Urbanization in the Latin American countries (BBVA, 2017) ............................................................. 33 
XI 
 
Figure 25 GDP of South American countries per capita, from 1950 to 2016 (United Nations, World 
Urbanization Prospects: The 2018 Revision, 2018) ................................................................................... 34 
Figure 26 Urbanization in African (1950-2050) (Daniel Hoornweg, Mila Freire, 2013). .................................... 35 
Figure 27 Share of the urban population globally (UNCTAD, 2018) .................................................................. 38 
Figure 28 This figure shows the projections of the world’s urban population ((EEA), European Environment 
Agency, 2014) ............................................................................................................................................ 38 
Figure 29 The urban population of the world by region, 1970-2017 (Create by Author) and (Data by (worldbank, 
2018)) ......................................................................................................................................................... 39 
Figure 30 The Radar chart of the urban population of the world by Region (Create by Author) and (Data by 
(worldbank, 2018)) ..................................................................................................................................... 39 
Figure 31 Share of greenhouse gas emissions by countries (Schmidt, 2015). ...................................................... 51 
Figure 32 significant forces that participate in the urban development (by the author)........................................ 54 
Figure 33 Urban frames, layers, and the formation of urban spaces and structures (by the author) ..................... 54 
Figure 34 The three main pillars of the Green Growth theory (by the author) ..................................................... 55 
Figure 35, intracity transport patterns (by the author) .......................................................................................... 56 
Figure 36 Major factors with significant roles in the sustainability area (Brand, 2005) ....................................... 56 
Figure 37 Engineering social behavior towards sustainability issues (by the author) .......................................... 57 
Figure 38 engineering social space to reshape environmental space (by the author) ........................................... 58 
Figure 39 The influential factors for delivering a better sense of place in the land use planning act (by the 
author) ........................................................................................................................................................ 59 
Figure 40 A planned and infrastructured suburb (Fettmann, 2019) ...................................................................... 60 
Figure 41 A slum without basic infrastructures closed to the developed zone with big-buildings and best 
infrastructures (Villa, 2017) ....................................................................................................................... 60 
Figure 42 A conceptual model of Stone-shaped 3D-printed rental homes in the Netherlands (Davis, 2018) ...... 61 
Figure 43 A conceptual model of Stone-shaped 3D-printed rental homes in the Netherlands, by Houben/Van 
Mierlo architects (Davis, 2018) .................................................................................................................. 61 
Figure 44 The conceptual model of developing urban zones (by the author) ....................................................... 63 
Figure 45 a sample model of a compact city (Sang-gil, 2018) ............................................................................. 65 
Figure 46 Decreasing the occupation of urban spaces by increasing urban density and High-rise building  (Saleh 
Abdullahi, Biswajeet Pradhan, Abubakr Al-sharif, 2017) .......................................................................... 66 
Figure 47 Potentials of urban horizontal growth and its effects on the urban activities and land consumption (by 
the author) .................................................................................................................................................. 66 
Figure 48 The conceptual pattern of Sprawl growth  (by the author) ................................................................... 68 
Figure 49 A shift from the human‘s traditional lifestyle to the new and modern lifestyle. Designed by the author. 
And the first picture from the right at the top of this presentation was acquired from (Goswami, 2020), 
and the last picture from the left at bottom of this presentation was acquired from (de labour, 2020) ...... 75 
Figure 50 looking at the cities from the lens of technological urbanization  (by the author) ............................... 76 
Figure 51 Different densities of land consumption between the urban, suburban, and rural areas (by the author)
 .................................................................................................................................................................... 77 
XII 
 
Figure 52 Living on the water, the new housing development project for the middle class, Dahaka, Pakistan, 
(Shafi, 2011). .............................................................................................................................................. 77 
Figure 53 A sample model of compacted and multifunctional building regarding the principles of smart growth 
(mixed-use) (barbara-porada, 2013) ........................................................................................................... 80 
Figure 54 Guidelines for urban authorities and private Sectors (by the author) ................................................... 81 
Figure 55 Conceptual model of a smart city according to the principles of the Smart Growth theory (Schilling, 
2015) .......................................................................................................................................................... 82 
Figure 56 A conceptual representation of land use planning (by the author) ....................................................... 86 
Figure 57 The main pillars engaged in the evolution of land use planning (by the author) .................................. 86 
Figure 58 Change and progress of land use quantitatively and qualitatively (by the author) ............................... 87 
Figure 59 Develop and increase of land use activities considering time, place, and space (by the author) .......... 88 
Figure 60 The interaction and communication between human's real-world and cyberspace (by the author) ..... 88 
Figure 61 General parts of land administration system (by the author) ................................................................ 90 
Figure 62 The important factors in the determination of activities for land parcels  (by the author) ................... 92 
Figure 63 Conceptual networking model to have exact data sharing between sectors in a system (by the author)
 .................................................................................................................................................................... 94 
Figure 64 Isard’s longitudinal and transverse matrix (by the author) ................................................................. 104 
Figure 65 A simple view of the Lorenz Curve (by the author) ........................................................................... 105 
Figure 66 Iran’s population, Source: the column chart designed by the author, and the data from the (Statistical 
Center of Iran, 1956-2017). ...................................................................................................................... 113 
Figure 67 Iran’s urban and rural population. Source: the graph designed by the author, and the data from the 
(Statistical Center of Iran, 1956-2017). .................................................................................................... 114 
Figure 68, The migration of urban or rural areas. Source: the column chart designed by the author, and the data 
from the (Statistical Center of Iran, 1956-2017). ..................................................................................... 115 
Figure 69, The urban-rural migration at the national level in percent. Source: the graph designed by the author, 
and the data from the (Statistical Center of Iran, 1956-2017). ................................................................. 115 
Figure 70 The total population of Mazandaran. Source: the graph designed by the author 2021, and the data 
from the (Statistical Center of Iran, 1956-2017). ..................................................................................... 117 
Figure 71 The growth of populations in the urban and rural areas of the Mazandaran metropolitan area. Source: 
the graph designed by the author, and the data from the (Statistical Center of Iran, 1956-2017). ........... 118 
Figure 72 The changes in the growth of urban-rural population at the Sari city and district levels Source: the 
graph designed by the author, and data from the (Statistical Center of Iran, 1956-2017). ....................... 118 
Figure 73 The linear graph of the population changes at the national, regional, and local levels (by the author)
 .................................................................................................................................................................. 120 
Figure 74 The column chart of the population changes at the national, regional, and local levels (by the author)
 .................................................................................................................................................................. 120 
Figure 75 The column chart of the population's elasticity rate at the national, regional, and local levels (by the 
author) ...................................................................................................................................................... 123 
Figure 76 The linear graph of the changes in the elasticity rate of the populations at the national, regional, and 
local levels (by the author) ....................................................................................................................... 124 
XIII 
 
Figure 77 The projected population growth in Iranian cities using the Modified Exponential Model at the 
national level (by the author) .................................................................................................................... 127 
Figure 78 The predicted population growth of the Mazandaran metropolitan area for the years 2026 (by the 
author) ...................................................................................................................................................... 129 
Figure 79 The predicted population growth of Sari city between 2016-2026 (by the author) ............................ 130 
Figure 80, The imbalance between the actual size of the population with the ideal size of the population of cities 
in the Mazandaran metropolitan area considering the results of Zip's law; between 1976- 1986, Iran (by 
the author) ................................................................................................................................................ 136 
Figure 81 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of 
Rank-Size Rule between 1976- 1986, Iran (by the author) ...................................................................... 137 
Figure 82 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area 
(by the author) .......................................................................................................................................... 138 
Figure 83 The imbalance between the actual size of the population with the ideal size of the population of cities 
in the Mazandaran metropolitan area considering the results of Zip's law; between 1986- 1996, Iran (by 
the author) ................................................................................................................................................ 141 
Figure 84 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of 
Rank-Size Rule between 1986- 1996, Iran (by the author) ...................................................................... 142 
Figure 85 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area 
(by the author) .......................................................................................................................................... 143 
Figure 86 The imbalance between the actual size of the population with the ideal size of the population of cities 
in the Mazandaran metropolitan area considering the results of Zip's law; between 1996- 2006, Iran (by 
the author) ................................................................................................................................................ 147 
Figure 87 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of 
Rank-Size Rule between 1996- 2006, Iran (by the author) ...................................................................... 147 
Figure 88 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area 
(by the author) .......................................................................................................................................... 149 
Figure 89 The imbalance between the actual size of the population with the ideal size of the population of cities 
in the Mazandaran metropolitan area considering the results of Zip's law; between 2006- 2016, Iran (by 
the author) ................................................................................................................................................ 152 
Figure 90 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of 
Rank-Size Rule between 2006- 2016, Iran (by the author) ...................................................................... 152 
Figure 91 The percent of the spatial distribution of populations in the cities of the Mazandaran metropolitan area  
(by the author) .......................................................................................................................................... 154 
Figure 92 Numeric growth of cities in the Mazandaran metropolitan area from 1956 to 2016 (by the author) . 155 
Figure 93 The proportion of the numbers of cities and size of the population to the total proportion in percent. 
The numbers between 1-7 horizontally refer to the decades in Table 27 (by the author) ......................... 156 
Figure 94 Increasingly difference between the size and rank of the first city with the smallest city according to 
the results of the Rank-Size roll  (by the author) ...................................................................................... 157 
Figure 95  The geographical position and borders of the Mazandaran metropolitan area in the 1960s (by the 
author) ...................................................................................................................................................... 158 
XIV 
 
Figure 96 The geographical position and borders of the Mazandaran metropolitan area in 2020 (by the author)
 .................................................................................................................................................................. 158 
Figure 97 The visual comparison of the changed borders from 1960 to 2020, By author 2020 (by the author) 158 
Figure 98 The L.Q of the activities of Sari city at the national level, 1966-2016 (by the author) ...................... 163 
Figure 99 The L.Q of the economic activities of Sari city at the regional level, 1986-2016 (by the author) ...... 165 
Figure 100 The L.Q of the activities of Sari city at the regional level, 1986-2016 (by the author) .................... 166 
Figure 101 The matrix of the activities of Sari city at the national level between 1966-1976 (by the author) ... 167 
Figure 102 The matrix of the activities of Sari city at the national level between 1976-1986 (by the author) ... 169 
Figure 103 The matrix of the activities of Sari city at the national level between 1986-1996 (by the author) ... 171 
Figure 104 The matrix of the activities of Sari city at the national level between 1996-2006 (by the author) ... 173 
Figure 105 The matrix of the activities of Sari city at the national level between 2006-2016 (by the author) ... 175 
Figure 106 the results of the Lorenz Curve and Gini Coefficient for the decade 1986 (by the author) .............. 178 
Figure 107 the results of the Lorenz Curve and Gini Coefficient for the decade 1996 (by the author) .............. 181 
Figure 108 the results of the Lorenz Curve and Gini Coefficient for the decade 2006 (by the author) .............. 184 
Figure 109 the results of the Lorenz Curve and Gini Coefficient for the decade 2016 (by the author) .............. 188 
Figure 110 The conceptual model of the levels of urban management in Iran (by the author) .......................... 198 
Figure 111 Members of the first Iranian Parliament (Library W. D., 1906) ....................................................... 203 
Figure 112 Supplying water using water tanks (Najafzadeh, 2021) ................................................................... 204 
Figure 113 Lalehzar Street, Tehran in 1926s. (Gheissari, 2011) ........................................................................ 205 
Figure 114 Persian Shops, 1905. A peep into the bazaar of Isfahan. In these open shops, all goods are exposed to 
view, and the passer-by is invited to take a seat and inspect (Mary Hume-Griffith, Dr. Albert Hume-
Griffith, 1909) .......................................................................................................................................... 205 
Figure 115 A Street in Kerman, in 1907 leading into the long covered bazaar (Mary Hume-Griffith, Dr. Albert 
Hume-Griffith, 1909) ............................................................................................................................... 206 
Figure 116 A bazaar in the city of Mashhad (Sykes, 1921) ................................................................................ 206 
Figure 117 A house-building project in Persia, 1904s, (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909)
 .................................................................................................................................................................. 207 
Figure 118: The interactions between politics, law, and spaces (by the author) ................................................. 208 
Figure 119, Panorama of Tehran, in 1892s, (Curzon, 1892) .............................................................................. 210 
Figure 120 Royal square at Isfahan, in 1909s, (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) ........... 210 
Figure 121 The city of Isfahan from the north side (Sykes, 1921) ..................................................................... 211 
Figure 122 Panorama of Shiraz, in 1909s. (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) ................. 211 
Figure 123 Mashhad, the sacred city of Persia. The picture was taken from the city wall and shows the mosque 
of Gauharshad (left), and the golden dome (center) in the background (Sykes, 1921) ............................ 212 
Figure 124 The Amirchakhmagh square in Yazd city (Sykes, 1921) ................................................................. 212 
Figure 125  Tabriz city (Sykes, 1921) ................................................................................................................ 213 
Figure 126 Constructing new roads in the city of Tehran by Reza Shah in 1946  (Mohammad Reza Pourzargar, 
Parichehr Moafi Ghaffari, Maryam Amjadi, 2018) .................................................................................. 214 
Figure 127 Providing water infrastructures in the city of Tehran city by Reza Shah in 1945 (Mohammad Reza 
Pourzargar, Parichehr Moafi Ghaffari, Maryam Amjadi, 2018) .............................................................. 215 
XV 
 
Figure 128 The walls of Tus city (Sykes, 1921) ................................................................................................. 216 
Figure 129 Dowlet gate, Tehran 1902 (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909)........................ 217 
Figure 130 The Mosque gate, City of Kerman (Sykes, 1921) ............................................................................ 217 
Figure 131 City Building in a new and modern form (left), under Pahlavi Dynasty, city of Tehran (by the author)
 .................................................................................................................................................................. 218 
Figure 132 City Building in a new and modern form (left), during Pahlavi Dynasty, the city of Shiraz (by the 
author) ...................................................................................................................................................... 218 
Figure 133 Design and layout of public squares in new towns during Reza Shah Pahlavi (Eckart Ehlers, Willem 
Floor, 1993) .............................................................................................................................................. 219 
Figure 134 The sectors that are under effects of the national development plans directly and indirectly (by the 
author) ...................................................................................................................................................... 220 
Figure 135 Modern Tehran during Pahlavi Dynasty (Siyavosh, 2013) .............................................................. 224 
Figure 136 Iran's annual economic growth rate 1960-2019, (worldbank.org, 2021) .......................................... 225 
Figure 137 The percent of amendments or enacted urban development legislation and regulations between 1280-
1359 (by the author) ................................................................................................................................. 226 
Figure 138 Number of rural areas that have changed into towns (by the author) ............................................... 230 
Figure 139 Numerical growth of cities and towns in Iran from Pahlavi dynasty between (1956-1976), to the 
republic Iran between (1976-2016) (by the author) .................................................................................. 231 
Figure 140 Interactions between organizations, authorities, and planners during planning practice in a 
centralized system (by the author) ............................................................................................................ 236 
Figure 141 Iran's GDP growth by decades 1960-2019, the graph provided by the author, and the data from 
(worldbank.org, 2021) .............................................................................................................................. 239 
Figure 142 The dimensions of studying Iran’s planning system (by the author) ................................................ 242 
Figure 143 Numbers of enacted conperehencive plans for the development of Iranian cities (by the author) ... 246 
Figure 144 Numbers of cities that have faced contradictions in both Comprehensive Plan and Detailed Plan (by 
the author) ................................................................................................................................................ 247 
Figure 145 The systematic direct effects of national plans on the local plans in a centralized system (by the 
author) ...................................................................................................................................................... 247 
Figure 146: Landsat image of the 1972s (USGS, 2021) ..................................................................................... 253 
Figure 147: Landsat images of the 1988s  (USGS, 2021) .................................................................................. 253 
Figure 148: Landsat images of the 1999s  (USGS, 2021) .................................................................................. 253 
Figure 149: Landsat images of the 2010s  (USGS, 2021) .................................................................................. 253 
Figure 150: Landsat images of the 2020s  (USGS, 2021) .................................................................................. 253 
Figure 151: The defined color ranges for the land covers (Clarklabs, 2020) ...................................................... 254 
Figure 152: The research framework for remote sensing and modelling (by the author) ................................... 259 
Figure 153: The classification and reclassification of the provided landsat images (by the author) .................. 260 
Figure 154: The classified land covers change of Sari city for the year 1972 (by the author) ............................ 260 
Figure 155: The classified land covers change of Sari city for the year 1988 (by the author) ............................ 261 
Figure 156: The classified land covers change of Sari city for the year 1999 (by the author) ............................ 261 
Figure 157: The classified land cover changes of Sari city for the year 2010 (by the author) ............................ 262 
XVI 
 
Figure 158: 2020 The classified land cover changes of Sari city for the year 2020 (by the author) ................... 262 
Figure 159: The simple dynamic model of the growth of Sari city that follows nodes and road development  (by 
the author) ................................................................................................................................................ 264 
Figure 160: The built-up area within of the official border of the city (by the author) ...................................... 264 
Figure 161 The physical growth stages of Sari city (by the author) ................................................................... 265 
Figure 162 The physical growth of the city of Sari considering all land uses from 1972 to 2020 (by the author)
 .................................................................................................................................................................. 265 
Figure 163: Changes of the area of Sari city including: Built-up, Vegetation, Uncultivated and water body over 
the last decades (by the author) ................................................................................................................ 266 
Figure 164 The physical growth of Sari city combined by the land cover changes from 1972 to 2020 (by the 
author) ...................................................................................................................................................... 266 
Figure 165: Physical growth of Sari city over the last decades (by the author) .................................................. 268 
Figure 166: Changes in all land covers and comparison with each other between 1972-2020 (by the author) .. 269 
Figure 167 The graphical demonstration of land-use changes from one type to the other types (by the author) 270 
Figure 168 The map of changed land covers from 1972 to 2020 (by the author) ............................................... 271 
Figure 169, The radar graph of land values (by the author) ............................................................................... 272 
Figure 170 The Cubic Trend map for the change of Vegetation to the Built-up area (by the author) ................ 274 
Figure 171 Illustration of the Built-up area, particularly roads (by the author) .................................................. 275 
Figure 172 The projected growth of the Built-up area in the following decades 2030, 2040, and 2050 (by the 
author) ...................................................................................................................................................... 276 
Figure 173 Projected land use changes for the decade 2030 (by the author) ...................................................... 277 
Figure 174 Projected land-use changes for the decade 2040 (by the author)...................................................... 278 
Figure 175 Projected land use changes for the decade 2050 (by the author) ...................................................... 279 
Figure 176 The hybrid map of the geographical location of Sari city in the Mazandaran Metropol (by the author)
 .................................................................................................................................................................. 283 
Figure 177 The hybrid map of the sphere of influence of Sari city at the local and regional levels (by the author)
 .................................................................................................................................................................. 283 
Figure 178 The hybrid view over the studied area (by the author) ..................................................................... 284 
Figure 179 The hybrid map of the physical growth of Sari between 1921-2006 (by the author) ....................... 284 
Figure 180 The hybrid map of the physical growth of Sari city between 1972-2020 (by the author) ................ 285 
Figure 181 The defined reference system for the created grid sheets (by the author) ........................................ 286 
Figure 182 The grid 0 from zone one and grid one from zone two (by the author) ............................................ 288 
Figure 183 The grids 6, 7, 8, 13, 14, and 15 from zone two (by the author) ...................................................... 289 
Figure 184 The grids 15, 23, 24, 25, and 26 from zone two (by the author) ...................................................... 289 
Figure 185 The grids 27, 40, and 41 from zone two (by the author) .................................................................. 290 
Figure 186 The grids 38, 39, 40, 41, 52 and 53 from zone two (by the author) ................................................. 290 
Figure 187 The grids 37, 51, 52, and 53 from zone two (by the author) ............................................................ 291 
Figure 188 The grids 49, and 50 from zones one and two, and grids 51 and 61 from zone 2 (by the author) .... 291 
Figure 189 The grids 60, 61, 63 nad 64 from zones three (by the author) .......................................................... 292 
Figure 190 The grid 67 from zones three (by the author) ................................................................................... 292 
XVII 
 
Figure 191 The grid 70 from zones three (by the author) ................................................................................... 293 
Figure 192 The grid 73 from zones three (by the author) ................................................................................... 293 
Figure 193 The grid 75 from zones three (by the author) ................................................................................... 294 
Figure 194 The grid 72 from zones three (by the author) ................................................................................... 294 
Figure 195 The grids 68 and 69from zones three (by the author) ....................................................................... 295 
Figure 196 The 66 and 65 from zones three (by the author) ............................................................................... 295 
Figure 197 The grids 56, 57, 58, 59 and 62 from zones three (by the author) .................................................... 296 
Figure 198 The grids 54, 55, and 56 from zones three (by the author) ............................................................... 296 
Figure 199 The grids 54, 55, and 56 from zonesone and  three, and grids 28, 29, 30, 42, 43, and 44 from the 
zone one (by the author) ........................................................................................................................... 297 
Figure 200 The grid 28 from zone one (by the author) ....................................................................................... 297 
Figure 201 The grids 54, 55, and 56 from zones three 16, 17, 28, 29,and 30 from zone one (by the author) .... 298 
Figure 202 The grids 2, 3, 9, and 56 from zones one (by the author) ................................................................. 298 
Figure 203 The grids 0, 2, 3, and 4 from zones one (by the author) ................................................................... 299 
Figure 204 The grid 0 from zone one and two, and grid 1 from zone two (by the author) ................................. 299 
Figure 205 The land use map Sari city. The map provided by author, and the data from (The Ministry of 
Housing, Road, and Urban Development, 2015) ...................................................................................... 300 
Figure 206 Urban density and its effect on the size of land when subdividing (by the author) .......................... 301 
Figure 207 The map of land values combined with the changed land parcels (by the author) ........................... 302 
Figure 208 Tabarestan is a mix-use development project horizontally integrating multifamily housing and retail, 
clinics, and other public services. This area is located in zone one of the city Sari (by the author) ......... 304 
Figure 209, An exemplar uncontrolled and sprawl area that is located in zone three, in the buffer 1000 meters, 
with growing single-use buildings projects on land parcels without accessibility to the basic services. 
These building projects started by private investors without getting building permits (by the author) .... 304 
Figure 210 This big orchard is destroyed for starting a building project and and subdivided into many parcels 
(by the author) .......................................................................................................................................... 305 
Figure 211 The subdivided land parcels in zone one considering the three classes of buffers (by the author) .. 306 
Figure 212 The percent of the subdivided land parcels in zone one considering the three classes of buffers (by 
the author) ................................................................................................................................................ 307 
Figure 213 The subdivided and under construction land parcels in zone one considering the three classes of 
buffers (by the author) .............................................................................................................................. 308 
Figure 214 The percent of the subdivided and under construction land parcels in zone one (by the author) ..... 308 
Figure 215 The subdivided and build up land parcels in zone one considering the three classes of buffers (by the 
author) ...................................................................................................................................................... 309 
Figure 216 The percent of the subdivided and build up land parcels in zone one considering the three classes of 
buffers (by the author) .............................................................................................................................. 310 
Figure 217 The geographical position of the Tajan river considering the official border to the Sari city (by the 
author) ...................................................................................................................................................... 311 
Figure 218 The presentation of the density of big buildings in the inner zone of Sari city (by the author) ........ 312 
XVIII 
 
Figure 219 The geographical position of the Tajan river considering the physical body of Sari city (by the 
author) ...................................................................................................................................................... 312 
Figure 220 The road networks of Sari city (by the author) ................................................................................. 313 
Figure 221 The subdivided land parcels in zone two considering the three classes of buffers (by the author) .. 314 
Figure 222 The percent of the subdivided land parcels in zone two (by the author) .......................................... 314 
Figure 223 The subdivided and under construction land parcels in zone two considering the three classes of 
buffers (by the author) .............................................................................................................................. 315 
Figure 224 The percent of the subdivided and under construction land parcels in zone two (by the author) ..... 316 
Figure 225 The subdivided and built-up land parcels in zone two considering the three classes of buffers (by the 
author) ...................................................................................................................................................... 317 
Figure 226 The percent of the subdivided and built-up land parcels in zone two (by the author) ...................... 317 
Figure 227 The peripheral areas attached to the physical body of Sari city (by the author) ............................... 319 
Figure 228 The proposed roads network of Sari city (by the author) ................................................................. 319 
Figure 229 The layers of the physical body of Sari city (by the author)............................................................. 320 
Figure 230 The subdivided land pa rcels in zone three considering the three classes of buffers (by the author) 321 
Figure 231 The percent of the subdivided land parcels in zone three (by the author) ........................................ 321 
Figure 232 The subdivided and under construction land parcels in zone three considering the three classes of 
buffers (by the author) .............................................................................................................................. 322 
Figure 233 The percent of the subdivided and under construction land parcels in zone three (by the author) ... 323 
Figure 234 The subdivided and built-up land parcels in zone three considering the three classes of buffers (by 
the author) ................................................................................................................................................ 324 
Figure 235 The percent of the subdivided and built-up land parcels in zone three (by the author) .................... 325 
Figure 236 The area of the subdivided land parcels considering the three zones  (by the author) ..................... 326 
Figure 237 The area of the subdivided and under construction land parcels considering the three zones (by the 
author) ...................................................................................................................................................... 327 
Figure 238 The area of the subdivided and built-up land parcels considering the three zones (by the author) .. 328 
Figure 239 The summed area of the changed land uses considering the three classes (by the author) ............... 329 
Figure 240 The map of the physical growth of Sari city (by the author) ............................................................ 336 
Figure 241Controlling the rapid regional migration to the big cities by the small-sized cities (by the author) .. 342 
Figure 242 A planned building progect to control unplanned land use changes (by the author) ........................ 343 
 
 
 
 
 
 
XIX 
 
Tables 
Table 1 Population categorization in the Mazandaran metropolitan area (Statistical Center of Iran, 2016) .......... 3 
Table 2 Calcification of Iran’s urban areas based on the population (by the author) ............................................. 4 
Table 3 The total population of the Mazandaran metropolitan area. Source: Analysed and classified by the 
author, 2021, and raw data from the (Statistical Center of Iran, 1956-2017). .............................................. 5 
Table 4 The changes of urban-rural population growth at the Sari city and district levels. Source: Analysed and 
classified by the author, 2021, and raw data from the (Statistical Center of Iran, 1956-2017) .................... 7 
Table 5 Comprising the cities with sprawl growth versus the cities with compact growth (by the author) ......... 69 
Table 6 Iran’s population, Source: Analysed and classified by the author, 2021, and raw data from the 
(Statistical Center of Iran, 1956-2017). .................................................................................................... 113 
Table 7 Iran's urban and rural population changes, Source: Analysed and classified by the author, 2021, and the 
data from the (Statistical Center of Iran, 1956-2017). .............................................................................. 113 
Table 8 The migration of urban or rural areas. Source: Analysed and classified by the author, 2021, and the data 
from the (Statistical Center of Iran, 1956-2017). ..................................................................................... 114 
Table 9 The total population of the Mazandaran metropolitan area. Source: Analysed and classified by the 
author, and the data from the (Statistical Center of Iran, 1956-2017). ..................................................... 117 
Table 10 The population of the Mazandaran metropolitan area and rural area. Source: Analysed and classified 
by the author, and the data from the (Statistical Center of Iran, 1956-2017). .......................................... 117 
Table 11 The changes in the growth of urban-rural population at the Sari city and district levels. Source: 
Analysed and classified by the author, and the data from the (Statistical Center of Iran, 1956-2017). .... 118 
Table 12 Calculating the rate of populations growth and changes at the national, regional, and local levels (by 
the author) ................................................................................................................................................ 119 
Table 13 The elasticity rate of the populations at the national, regional, and local levels (by the author) ......... 123 
Table 14 The projected population change in Iranian cities between 2016-2026 using the Modified Exponential 
Model at the national level (by the author) .............................................................................................. 126 
Table 15 The projected population change in Iranian cities for the decades 2026 and 2036 using the Linear 
Regression Model at the national level (by the author) ............................................................................ 128 
Table 16 The prediction of population change using the Modified Exponential Model for the Mazandaran 
metropolitan area (by the author) ............................................................................................................. 128 
Table 17 The predicted changes in the population of the Mazandaran metropolitan area using the Linear 
Regression Model for the decades 2026-2036 (by the author) ................................................................. 129 
Table 18 The projected changes in the population of Sari city between 2016-2026 using the Modified 
Exponential Model  (by the author).......................................................................................................... 130 
Table 19 The predicted population growth in Sari city using the Linear Regression Model for the decades 2026-
2036 (by the author) ................................................................................................................................. 131 
Table 20 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of Mazandaran 
metropolitan area between decades 1976- 1986, Iran  (by the author) ..................................................... 135 
Table 21 The calcification of urban area based on the population in Iran (by the author) ................................. 138 
Table 22 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 1986- 1996, Iran (by the author) ................................................................... 140 
XX 
 
Table 23 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 1996- 2006, Iran (by the author) ................................................................... 145 
Table 24 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 2006- 2016, Iran (by the author) ................................................................... 150 
Table 25 Classifying the cities of the Mazandaran metropolitan area considering the population  (by the author)
 .................................................................................................................................................................. 154 
Table 26 Number of cities in the Mazandaran metropolitan area from 1956 to 2016, Iran (by the author) ....... 155 
Table 27 The proportion of the numbers of cities and size of the population to the total ratio, 1956-2016 (by the 
author) ...................................................................................................................................................... 156 
Table 28 The total share of the three basic economic activities at the city and national levels in the 1966s (by the 
author) ...................................................................................................................................................... 159 
Table 29 The rate of L.Q of Sari city at the national levels in the 1966s (by the author) ................................... 159 
Table 30 The total share of the three basic economic activities at the city and national levels in the 1976s (by the 
author) ...................................................................................................................................................... 159 
Table 31 The rate of L.Q of Sari city at the national levels in the 1976s (by the author) ................................... 159 
Table 32 The total share of the three basic economic activities at the city, county, regional and national levels in 
the 1986s (by the author) .......................................................................................................................... 160 
Table 33 The percent of the activities of Sari city at the city, county, regional, and national levels in the 1986s 
(by the author) .......................................................................................................................................... 160 
Table 34 The rate of L.Q of Sari city at the county, regional, and national levels in the 1986s (by the author) 160 
Table 35 The total share of the three basic economic activities at the city, county, regional and national levels in 
the 1996s (by the author) .......................................................................................................................... 160 
Table 36 The percent of the activities of Sari city at the county, regional, city, and national levels in the 1996s 
(by the author) .......................................................................................................................................... 161 
Table 37 The rate of L.Q of Sari city at the county, regional, and national levels in the 1996s (by the author) 161 
Table 38 The total share of the three basic activities at the city, county, regional and national levels in the 2006s 
(by the author) .......................................................................................................................................... 161 
Table 39 The percent of the activities of Sari city at the county, regional, and national levels in the 2006s (by the 
author) ...................................................................................................................................................... 161 
Table 40 The rate of L.Q of Sari city at the county, regional, and national levels in the 2006s (by the author) 161 
Table 41 The total share of the three basic activities at the city, county, regional and national levels in the 2016s 
(by the author) .......................................................................................................................................... 162 
Table 42 The percent of the activities of Sari city at the city, county, regional, and national levels in the 2016s 
(by the author) .......................................................................................................................................... 162 
Table 43 The rate of L.Q of Sari city at the county, regional, and national levels in the 2016s (by the author) 162 
Table 44 The rate of L.Q of the activities of Sari city at the national level, 1966-2016 (by the author) ............ 163 
Table 45 The rate of L.Q of the activities of Sari city at the regional level, 1986-2016 (by the author) ............ 165 
Table 46 The rate of L.Q of the activities of Sari city at the county level, 1986-2016 (by the author) .............. 166 
Table 47 The proportion of the activities of Sari city compared at the national level between 1966-1976 (by the 
author) ...................................................................................................................................................... 167 
XXI 
 
Table 48 The proportion of the activities of Sari city compared at the national level between 1976-1986 (by the 
author) ...................................................................................................................................................... 169 
Table 49 The proportion of the activities of Sari city compared at the national level 1986-1996 (by the author)
 .................................................................................................................................................................. 171 
Table 50 The proportion of the activities of Sari city compared at the national level 1996-2006 (by the author)
 .................................................................................................................................................................. 173 
Table 51 The proportion of the activities of Sari city compared at the national level 2006-2016 (by the author)
 .................................................................................................................................................................. 175 
Table 52 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors 
population and rank in the 1986s (by the author) ..................................................................................... 177 
Table 53 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors 
population and rank in the 1996s (by the author) ..................................................................................... 180 
Table 54 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors 
population and rank in the 2006s (by the author) ..................................................................................... 183 
Table 55 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors 
population and rank in the 2016s (by the author) ..................................................................................... 186 
Table 56 The rate of entropy of the spatial distribution of population and size of cities according to the actual 
population for the decade 1986s (by the author) ...................................................................................... 190 
Table 57 The rate of entropy of the spatial distribution of population and size of cities according to the 
population of Zipf's law for the decade 1986  (by the author) .................................................................. 190 
Table 58 The rate of entropy of the spatial distribution of population and size of cities according to the actual 
population for the decade 1996s (by the author) ...................................................................................... 191 
Table 59 The rate of entropy of the spatial distribution of population and size of cities according to the 
population of Zipf's law for the decade 1996 (by the author) ................................................................... 191 
Table 60 The rate of entropy of the spatial distribution of population and size of cities according to the actual 
population for the decade 2006s (by the author) ...................................................................................... 192 
Table 61 The rate of entropy of the spatial distribution of population and size of cities according to the 
population of Zipf's law for the decade 2006 (by the author) ................................................................... 192 
Table 62 The rate of entropy of the spatial distribution of population and size of cities according to the actual 
population for the decade 2016s (by the author) ...................................................................................... 193 
Table 63 The rate of entropy of the spatial distribution of population and size of cities according to the 
population of Zipf's law for the decade 2016 (by the author) ................................................................... 193 
Table 64 The trajectory of urban development in Iran and the main changes that happened between 1908 to 
2021 (by the author) ................................................................................................................................. 201 
Table 65 The main national implemented urban development policies between 1947 to 1987 (by the author) . 221 
Table 66 Number of rural areas that have changed into towns (National Statistics Centers, 2019) (by the author)
 .................................................................................................................................................................. 230 
Table 67 Growth of cities and towns with considering the implemented development plans before and after the 
revolution 1978 (by the author) ................................................................................................................ 231 
Table 68 The enacted development plans after the revolution 1979 (by the author) .......................................... 238 
XXII 
 
Table 69, The used time-series Landsat images (by the author) ......................................................................... 252 
Table 70: Land Cover Changes of the Sari City, 1972-2020 (by the author) ..................................................... 263 
Table 71: Population of Sari City, 1976-2016 (National Statistical Center of Iran, 2017) ................................. 263 
Table 72, The lassification of urban areas considering population, Iran (by the author) .................................... 268 
Table 73 Changes of land uses from one type to the other type (by the author) ................................................. 269 
Table 74: The projected land cover changes for the following decades 2030, 2040, and 2050 (by the author) . 275 
Table 75 Physical growth of the Built-up area for the projected decade 2030 (by the author) ........................... 277 
Table 76 Physical growth of the Built-up area for the projected decade 2040 (by the author) ........................... 278 
Table 77 Physical growth of the Built-up area for the projected decade 2050 (by the author) ........................... 279 
Table 78 The area of the subdivided land parcels in zone one considering the three classes of buffers (by the 
author) ...................................................................................................................................................... 307 
Table 79 The area of the subdivided and under construction land parcels in zone one considering the three 
classes of buffers (by the author).............................................................................................................. 308 
Table 80 The area of the subdivided and build up land parcels in zone one considering the three classes of 
buffers (by the author) .............................................................................................................................. 310 
Table 81 The area of the subdivided land parcels in zone two considering the three classes of buffers (by the 
author) ...................................................................................................................................................... 314 
Table 82 The area subdivided and under construction land parcels in zone two (by the author) ....................... 316 
Table 83 The area of the subdivided and built-up land parcels in zone two considering the three classes of 
buffers (by the author) .............................................................................................................................. 317 
Table 84 The area of the subdivided land parcels in zone three considering the three classes of buffers (by the 
author) ...................................................................................................................................................... 320 
Table 85 The area of the subdivided and under construction in zone three considering the three classes of buffers 
(by the author) .......................................................................................................................................... 323 
Table 86 The area of the subdivided and built-up land parcels in zone three considering the three classes of 
buffers (by the author) .............................................................................................................................. 325 
Table 87 The area of the subdivided land parcels considering the three zones (by the author) .......................... 327 
Table 88 The area of the subdivided and under construction land parcels considering the three zones (by the 
author) ...................................................................................................................................................... 328 
Table 89 The area of the subdivided and built-up land parcels considering the three zones (by the author) ..... 329 
Table 90 The summed area of the changed land uses considering the three classes (by the author) .................. 330 
 
 
 
 
 
XXIII 
 
ABBREVIATIONS 
MAXLIKE Maximum Likelihood 
LCM Land Change Modeler 
MLP multilayer perceptron 
TPM Transition Potential Modeling 
CA_MARK
Automaton Markov Mod 
OV 
GLP Global Land Project 
LULC Land Use and Land- Cover 
IGBP International Geosphere-Biosphere Project 
IHDP International Human Dimension Project 
UCP Urban Comprehensive Plans 
USDA Urban Sustainable Development Agendas 
USGS United States Geological Survey 
GIS Geographic Information System 
GDP Gross Domestic Product 
IMF International Monetary Fund 
UN United Nations 
SCP Sustainable Cities Program 
HDI Human Development Index 
WCED World Commission on Environment and Development 
UNESCAP The United Nations Economic and Social Commission for Asia and the Pacific 
Congrès Internationaux d’Architecture Moderne or International Congresses of Modern 
CIAM 
Architecture 
UNECE United Nations Economic Commission for Europe 
Yu the annual growth rate of urban population 
LQ Location Quotient 
𝑇𝑁𝑖 the number of employments in i sector locally 
𝑇𝑁𝑎 Overall employment locally 
𝐶𝑁𝑖 the number of employments in i sector regionally or nationally 
𝐶𝑁𝑎 Overall employment regionally or nationally 
Pi Frequency 
LnPi frequency of the natural logarithm 
TNC Total number cities 
NGOs Non-Governmental Organizations 
XXIV 
 
A Small urban area 
B1 Medium-sized cities (small-class) 
B2 Medium-sized cities (big-class) 
C1 Big cities (Medium-class) 
C2 Big and very big Cities 
 
 
 
 
 
 
 
 
XXV 
 
 
 
 
 
 
 
 
Chapter One 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1 
 
 
Urbanization and Sustainable 
Land Use Planning Challenges in 
the Mazandaran Metropolitan 
Area, 
the Case of Sari City  
 
 
1.1. Introduction 
Mazandaran metropolitan area is located in the north of Iran (4047964.32 m N, 
684691.47 m E) and has 60 cities with about 1,943,378 urban population (Statistical 
Center of Iran, 2016). In this region, from the south, we have mountains with Caspian 
Hyrcanian mixed forests ecoregion, and from the north, is close to the Caspian Sea. 
Mazandaran also has valuable potentials, including temperate climate, tourism 
attractions, extensive agricultural activities, livestock, industries, services, commercial 
and marine activities, and is near to Tehran1. Most of the cities in this metropolitan 
area have placed in the coastal area and near the rivers and just some towns are placed 
in the plains and mountains (Figure 3) (Mazandtarh, 2009). This thesis believes that, 
all the above factors have increased land use changes and consumptions in this 
metropole. Since the last decades, the urban system in this metropole has been faced 
with centralization, and there is an imbalance between the distribution of population 
and the size of cities. As a result, the big-sized cities became overpopulated. 
                                              
1 the capital of Iran 
2 
 
 
Figure 1 The geographical locations of counties and cities in the Mazandaran metropolitan area, (by the author) 
 
Table 1 Population categorization in the Mazandaran metropolitan area (Statistical Center of Iran, 2016) 
Groups of cities Number of cities Population size Percent 
C1 2 597619 30,75 
B2 2 442481 22,77 
B1 5 336289 17,3 
A 51 566989 29,18 
Sum 60 1943378 100 
 
 
3 
 
 
Figure 2 Classification of cities in the Mazandaran metropolitan area considering population (by the author) 
 
Table 2 Calcification of Iran’s urban areas based on the population (by the author) 
classes Urban Groups Population 
A Small cities less than 50000 
B1 Medium-sized cities (small-class) 50000 to 99999 
B2 Medium-sized cities (big-class) 100000 to 249999 
C1 Big cities (Medium-class) 250000 to499999 
C2 Big and very big Cities 500000 to 2000000 
 
Urban sprawling growth, land use changes and building without permits are the 
most critical issue and challenge in this metropole, especially in Sari city.  
 
4 
 
 
Figure 3 Topography of the Mazandaran metropolitan area and location of cities (by the author) 
 
A city's functions and spheres of influence will change by changes in the economic, 
agricultural, industrial, servicing, and political forces. And any change in the 
mentioned sectors leads to new changes in urban land uses and land consumption. As 
a result, any significant change in urban land uses and activities will affect a city's 
functions and spheres of influence. 
 
Table 3 The total population of the Mazandaran metropolitan area. Source: Analysed and classified by the author, 2021, 
and raw data from the (Statistical Center of Iran, 1956-2017). 
Decades 1956 1966 1976 1986 1996 2006 2016 
The total population 973964 1247102 1596565 2274862 2602008 2922432 3283582 
Cities 156329 301729 511787 897667 1223326 1554143 1936662 
Villages 817635 945373 1084778 1377195 1378682 1368289 1346920 
 
 
5 
 
 
Figure 4 Conceptual model of this thesis (by the author) 
6 
 
Regarding this thesis, studying these forces such as economic, agricultural, 
industrial, political, tourism, and servicing is required to provide new and reliable 
findings on the land-use changes in Sari city. 
 
 
Figure 5 The main forces of land use change (by the author) 
 
1.2. The city of Sari  
Sari is located on the east side of the Mazandaran metropolitan area and is the 
capital of this metropole. The area of the city is about 5013.37 hectares. About 347402 
people live in the official border of the city, and considering the peripheral area the 
city has about 504298 population. Sari has two different physical tissues, old and 
young. The old tissue is located in the core of the city, and the rest are young tissue 
that has been developed generally since 1935 by today. 
 
Table 4 The changes of urban-rural population growth at the Sari city and district levels. Source: Analysed and classified 
by the author, 2021, and raw data from the (Statistical Center of Iran, 1956-2017) 
1956 1966 1976 1986 1996 2006 2016 
Decades 
Total Population of Sari District 129168 204982 262877 370515 422461 490830 504298 
The Population of Sari City 27037 44547 70753 141020 195882 259413 347402 
 
7 
 
 
Figure 6 The geographical position of Sari county and Sari city (by the author) 
 
Despite implementing several development plans to control urban growth and 
prevent land use changes in Sari, the city still could not control this trend. The city has 
grown non-sustainable and uncontrolled on valuable farmlands, particularly in recent 
decades.  
Lack of clear and effective development policies have faced manage of cities and 
control of land resources with many difficulties locally and regionally. The current 
inefficient planning frameworks and ineffective administration performances made 
planning acts in Iran complex and most of development plans could not be 
implemented successfully. 
This thesis believes that identifying and studying the major factors of land-use 
changes of Sari city can help understand better the causes of this problem and propose 
effective solutions. 
 
8 
 
1.3. Research questions 
This research is issue-oriented and seeks to find the relationships among the 
mentioned forces that have increased and-use change and non-sustainable 
consumption of the farmlands. Accordingly, the questions are sorted into two groups. 
The main question is solution-oriented and seeks to solve the current issue. And the 
subsidiary questions are issue-oriented and seek a cause-and-effect relationship that 
has emerged from the problems mentioned above. 
1.3.1. The main question 
How can drive the uneven and destructive spatial pattern of urban development and 
intense land-use changes of Sari city toward a balanced and sustainable path? 
(Solution-oriented and directed question) 
1.3.2. The subsidiary questions 
- How is the pattern of urban development in the Mazandaran metropolitan area 
considering the population distributions in the cities and the place of Sari city in this 
region? (Correlational and directed question) 
- What development forces have intensified land use change and consumption in 
this city, and how? (Relational-analytical question) 
- What are the causes of instability and increasing land-use changes in Sari, and 
what factors play a role in exacerbating it? (Relational-analytical question) 
1.4. Research propositions 
- Centralization and inefficient planning system have progressed a ploralized form 
of regional development and intensified unequal distribution of opportunities, 
infrastructures, and facilities not only between urban and rural areas. 
- Sectoral development has unbalanced urban hierarchies in the Mazandaran 
metropolitan area and intensified urban-rural migration. 
- Centralization has affected the management of cities, and processes of planning 
and executing urban development plans negatively. 
9 
 
- Centralization, and sectoral development policies have intensified the urban 
sprawl growth, land-use change, and non-sustainable consumption of valuable 
agricultural lands. 
1.5. Research objectives 
1.5.1. General objective 
One of the main goals of this thesis is to identify the most influential forces of the 
non-sustainable urban development in this metropolitan area, particularly in Sari. And 
providing solutions for promoting a sustainable form of urban development, land-use 
planning, and land consumption in this metropolitan area, and particularly for the city 
of Sari? 
1.5.2. Specific objectives 
- Studying the nature and structure of the urban system and the spatial development 
of cities in the Mazandaran metropolitan area (with an emphasis on Sari). 
- Identifying the main forces that have intensified unequal urban-spatial 
development in this region and its effects on the instability of urban lands. 
- Review and assess the effects of the agricultural, industrial, political, services, and 
economic factors on the development pattern of cities, spatial-physical elements, and 
determine the impact of these factors on the sprawling growth, land use change, and 
land consumption. 
1.6. Methodology 
Methodologically, this thesis benefits from a commitment to methodological 
pluralism and seeks to alaysis the sity of Sari considering the defined objectives and 
questions. This thesis has studied the city of Sari and its relations at the regional and 
national levels. Several research methods were used in this study considering the aims 
and types of data. 
1.6.1. Methods and tools for data collection 
For the documentary studies this thesis has used books and scientific papers. 
10 
 
The quantitative and statistical data were collected from the following 
organizations and platforms: The Ministry of Housing, Roads and Urban 
Development; Statistics Center of Iran; National Budget and Planning Organization; 
Consulting firms as the provider of urban development plans, USGS, and Google 
earth. 
- The other part of the data that weren’t available collected through fieldwork and 
survey. 
1.6.2. Data analysis 
The following models were applied for analyzing the collected data,: Modified 
Exponential Model, Linear Regression Model, (LQ) Location Quotient – Lorenz 
Curve – The Rank – Size Rule –Zipf’s law, Entropy Index – The Gini coefficient, 
Isard's Longitudinal and Transverse Model – Location Coefficient- Land Change 
Modeler (LCM)- MAXLIKE, MARKOV, Cellular Automaton Markov Model 
(CA_MARKOV) 
The Excel software is used for running the above mentioned mathematical models 
and analyzing the data. 
For remote sensing and land use change modeling this thesis has used the software 
IDRISI Selva to analyze the physical growth of Sari city, land use changes and sprawl 
growth. Also, for mapping and generating thematic maps this thesis used the ArcGIS, 
GIS-Pro and Google Earth.  
 
11 
 
 
Figure 7 Conceptual model of this Ph.D. thesis considering methodology and data analysis processing (by the author) 
 
1.7. Innovation  
In order to provide reliable results, this thesis has studied these main economic 
forces, including agricultural, industrial, servicing, and political factors in this thesis. 
It has helped to understand better Iran’s urbanization considering the planning and 
political system, urban development policies, and urban development plans. 
Additionally, it was helpful to find the reasons of inefficient urban planning in Iran, 
and the forces of non-sustainable land use changes and land consumption. 
Accordingly, this thesis has studied all national development plans, official reports, 
and all implemented urban development policies and strategies since 1908 by 2020. 
1.8. Limitations  
Knowing about the limitations of this thesis can help to prevent any possible 
problems that can make the results invalid and unreliable. 
1.8.1. Personal limitations 
The thesis aims to obtain significant results through the correct data and provide 
solutions concerning the research questions and objectives. Therefore, this study is 
responsible or being neutral in all steps of this thesis. 
1.8.2. Research limitations  
Data limitations and collecting correct data are one of the main challenges of this 
thesis. Some types of data that were available, were collected from the published data 
12 
 
and reports by Iran’s national and regional organizations. But, for the group of data 
that were not available, the author collected them through field works, surveys, and 
also interviews with experts and managers. 
 
 
 
13 
 
 
 
 
 
 
 
Chapter Two 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14 
 
 
 
 
Urbanization, forces, changes, 
and challenges 
 
 
2.1. Anthropogenic urbanization 
Urbanization is the implication of changes in the human lifestyle. Changing and 
developing the human lifestyle from a caveman to a nomadic lifestyle helped emerge 
of tribes and small communities. Humans learned how to save themselves against 
natural threats and control and manage the natural environment. And later, they 
learned how to construct shelters, big towers, and castles with more security and 
defense systems. These places were the first sample cores of civilization and the small 
size of today's cities with hundreds or thousands of inhabitants. But later, civilization 
and more security helped humans to construct new settlements in open spaces, which 
finally led to the emergence of the first generation of today's cities and towns. From 
thousands of years ago, cities' type and form have been changed and developed 
depending on local conditions. This thesis regarded cities as an anthropogenic 
phenomenon, and their structure and forms have become more complicated 
considering humans' mind complexity and progressity. 
In continue this thesis has provided some definitions of "urbanization."  
Urbanization is one of the significant global trends that have been growing in most 
countries since the 1880s, concerning the agglomeration of population and socio-
economic changes (C. Weber, A. Puissant, 2003), (Antrop, 2004). 
15 
 
Urbanization is a social development with growth in the size of population and area 
of cities (T.V. Ramachandra, H. A. Bharath, M. V. Sowmyashree , 2013) (Yasuhiro 
Sato a, Kazuhiro Yamamoto, 2005). 
Urbanization is the result of complex and dynamic economic growth that happens 
at multiple scales of space and time (Thomas Elmqvist, Michail Fragkias, Julie 
Goodness, Burak Güneralp, Peter J.Marcotullio, Robert I. McDonald, Susan Parnell, 
2013), (Tim Dyson, 2011). 
2.2. The major aspects of the contemporary urbanization 
During the last decades, the non-sustainable urban growth has been faced the world 
with global issues. And depending on the local conditions, the intensity of its negative 
effects was different. Most of today’s urban issues are air pollution, urban disease, 
climate change, crime, overcrowdingn, and non-sustsinable land use changes  
(Gotham K. , 2012). Urbanization after the industrial revolution was very different 
from before. From the viewpoint of this thesis, the following aspects are the aspects 
that distinguish contemporary urbanization from the time before the industrial 
revolution: (1) scale, (2) rate, and (3) size.  
2.2.1. The scale of urbanization  
The scale of urbanization relates to population size, activities, economic growth, 
geographical location, and environmental limitation. Today's cities are very bigger 
and more agglomerated than the cities from before the 1880s. For example, today, 
there are about 36 megacities in the world that are massively agglomerated with more 
than ten million populations. For instance, the metropole Tokyo-Yokohama has more 
than 38 million populations in an area of 13,500 km2, which is bigger than Jamaica 
with 11,000 km2 Figure 8.  
16 
 
 
Figure 8 The distribution of the world population (Cox, 2021) 
As presented in the above graph, the most populous urban areas are the 36 
megacities, each with more than 10 million residents. Megacities receive outsized 
attention due to their influence in media, finance, and tourism, but they have only 
14.8% of the urban population and 8.3% of the world population. The other urban 
areas in Demographia World Urban Areas (between 500,000 and 10 million) account 
for 20.5% of the world population, while smaller urban areas have 27.3% and the rural 
regions 43.9%. 
2.2.2. The rate of urbanization  
The high rate of urban growth is the other considerable aspect of contemporary 
urbanization. According to the statistical data, the rate of urban population has been 
growing globally particularly since the 1950s (Figure 9) (Adesoji David JIBOYE, 
2011) (Giovana Mira de Espindola a, 2017). United Nations in the year 2010 
published the "World Urbanization Prospects" report and predicted that the urban 
population between 2010 – 2030 will grow by about 1.4 billion globally. Which 
accounts for about 60% of the world's population (Shen, Z., 2012). However, in 2020, 
more than 56.12% of the world’s population lived in urban areas (See Figure 10) (UN, 
2011). Therefore, this thesis predicts that the world’s urban population will be more 
than 60% by 2030. 
17 
 
 
Figure 9 The world’s urban population growth by region (Karen C. Seto, Roberto Sanchez-Rodrıguez, Michail Fragkias, 
2010) 
As presented in the above graph, the thin lines denote rates of change; the thick 
lines represent magnitudes. The dashed lines represent United Nations projections. 
 
Figure 10 Number of people living in urban and rural areas globally , 1960 to 2020 (ourworldindata, 2021) 
 
2.2.3. Urbanization and size of cities 
Since the 1950s, researchers have identified some major changes in urban areas that 
have intensified global issues, including changes in urban interactions, health, non-
18 
 
stop urban-rural migration, increase in urban population, and non-sustainable urban 
growth (Karen C. Seto, Roberto Sanchez-Rodrıguez, Michail Fragkias, 2010).  
According to the studies, the most rapid-urbanized regions are located respectively 
in Asia, Africa, Europe, and South America. But, it should be noted that the Western 
European countries and North America, because of industrialization and economic 
development, have experienced urban development some decades earlier than the 
other countries (Anett Hofmann, Guanghua Wan, 2013). For example, the 
demographic changes of the following cities from 1 million to 8 million has taken 
about 130 years for London, 45 years for Bangkok, 37 years for Dhaka, and 25 years 
for Seoul. In the 1970s, the numbers of megacities with 10 million populations or 
more were not more than three cities. But today, we have about 38 megacities, which 
will increase to 41 cities by 2030. Also, up to the 1970s, just about 15b"large cities" 
were in the world, but today we have 43 big cities, which are projected to be about 63 
cities by 2030. Additionally, medium – and small-sized cities have also grown 
simultaneously (see Figure 11) (Thomas Elmqvist, Michail Fragkias, Julie Goodness, 
Burak Güneralp, Peter J.Marcotullio, Robert I. McDonald, Susan Parnell, 2013). 
 
Figure 11  Classification of the urban population considering size and number of cities globally, between1970 to 2030 
(United Nations, 2014). 
19 
 
2.3. Drivers of urbanization  
Analyzing socioeconomic changes help to identify some significant drivers of 
urbanization and also understand this process better. Usually, the reason for the 
migration of people from rural to urban refers to their needs and goals. For this group 
of people, migration can be an option to reach their goals or meet their needs better 
and easier than where they live. The advantages of a destination encourage people to 
migrate, or some disadvantages of where they live have forced them to migrate.  
 
Figure 12 Conceptual model of migrations between places within space and time (by the author) 
 
Hence, this thesis studies these issues considering the factors of time and place. As 
represented in the above conceptual model of the migration (Figure 12), there are two 
places: 1- The start point and 2- The stop point. The start point is where persons want 
to move from one place to another, which can be an urban or rural area. And the Stop 
point refers to a destination. It should be noted that considering the factor of time, 
migrations can be temporary or permanent. And space contains all of them, including 
people, places, mobility, and time. 
Of course, needs and how people meet their needs will affect their decisions and 
places to migrate. And a need can change by change in the social-economic sectors. 
20 
 
And most of the changes in the social-economic sectors occur under development 
policies, which are generally made by policymakers.  
These elements have two different types of connections as follow: 1- Internal 
connections and 2- External connections  
1- The internal connections refer to a linear relation and interaction between 
the elements in a one-dimensional space Figure 13. 
 
 
Figure 13 Internal connections and interactions among elements in an one-dimensional space (by the author) 
 
1. The external connections refer to the relations and interactions between 
elements and spaces in multiple-dimensional spaces. Here, the elements are 
the junctions that provide a possibility for connecting and linking many 
spaces together. They establish multi connections between elements for 
"effecting on" or "to be affected from" (Figure 14). As a result, they provide 
multi circular flows and interactions between spaces to create multiple 
spaces. Multiple spaces can be grouped and classified. And each group can 
21 
 
include many spaces but may belong to other groups or another bigger 
group. 
 
 
Figure 14 In- External connections and interactions between spaces and elements in multiple dimensional spaces (by the 
author) 
 
For example, implementing an ineffective urban development policy in a place can 
negatively affect other places’ development of a region. It means implementing an 
ineffective development policy can, through the junctions, affect spaces and even 
change them. In this regard, this thesis believes that, increasing urban-rural migration 
follows the above rule. Implementing non-sustainable development policies, unequal 
distribution of resources, and attention to cities more than villages have increased 
inequality, urban-rural migration, and created different landscapes of development. 
Furthermore, this study has provided some statistical data that helps understand better 
the drivers of urbanization and how the proportion of the urban-rural population has 
ended in the benefit of the cities. 
22 
 
Considering the report of the United Nations, rural areas had about 442.45 million 
people, and urban areas had about 18.92 million population before 1500 BC2. In other 
words, about % 95.9 of the world's population lived in rural areas and %4.1 in urban 
areas. 
Between 1500 – 1600, rural areas had about 525.15 million population, and in 
urban regions with a %1.1 increase had about 28.82 million people. 
Between 1600 – 1700, rural areas had about 527.41 million people and urban areas 
with a %0.1 increase had about 30.75 million population. 
Between 1700 – 1800, rural areas had about 917.56 million population and urban 
areas about 72.26 million people. 
Between 1800-1900, rural areas had about 1.38 Milliard people and urban areas 
about 270.6 million. 
Between 1900 – 2000, about 3.28 milliard people lived in rural and about 2.87 
milliard people in urban areas. The world was faced with an extreme decrease in 
the rural population, and a remarkable increase in the urban population (Figure 
15). It is projected that, about 3.09 milliard people will be settled in rural areas by the 
2050s, and 6.68 milliards in urban zones.  
Diagrammtitel
8000
6000 6068
4000
3028 3009 Rural
2000 2087 Urban
1038
442,45 525,15 527,41
917,56
0 18,92 28,82 30,75 72,26 270,6
Befor 1500 1600 1700 1800 1900 2000 2050
Centuries
 
Figure 15 Urban and rural demographic changes over centuries (ourworldindata, 2021) 
                                              
2 before Christ 
23 
 
Million
 
Figure 16 Percentage of the global population living in urban areas from 1950 to 2050 (World Health Organization, 
2018) 
 
Between the 1500th and early the1700th, in general political factors, military 
power, geographical location, trade and environmental potentials had played 
considerable roles in the emergence and development of cities. About more than 90 
percent of people worked on farmlands, which has escalated the population of rural 
areas. The population change between these centuries was very low Figure 15. 
Since the middle of the 1700th occurred, the first significant growth change in the 
rate of the urban population. Particularly after the beginning of the industrial 
revolution Figure 15. The Industrial Revolution has progressed urbanization by 
providing new job opportunities but led to the massive migration of people from rural 
to urban areas. Also, the emergence of philosophers and economic theoreticians like 
Karl Marx with new ideas for reforming political structures and economic systems 
were the other primary drivers of urbanization, particularly in western countries. 
Capitalism and moving toward economic prosperity through the construction of 
heavy, semi-heavy, and light industries, massive production, and promotion of 
consumerism were the other forces that have accelerated urbanization. On the one 
hand, constructing thousands of factories around urban areas had increased the need 
24 
 
for new workers. And on the other hand, these had increased the needs to new 
educational, health, transportation, and entertainment infrastructures and new 
buildings for settling new migrants. So, these factors have developed urbanization and 
expanded urban growth. But, rural areas became just a place for producing agricultural 
goods to provide the needed daily foods of cities. 
Technological development is the other driver of urban growth that has progressed 
urbanization remarkably. The development of new transportation systems has 
provided comfortable, faster, and secure vehicles, which have decreased the time of 
trips and increased the transport of people. Also has enabled people to have jobs in 
other places far from where they live. It also has developed the interactions between 
cities at the regional or national and global levels, and reformed international 
economic and political systems. 
It should be noted that, the revolutionary effects of technological development are 
not limited to transportation systems. Technological development has changed today’s 
lifestyle, communications, and created new social and cultural values. For example, 
new generations of smartphones, social media, and online marketing have changed or 
even, in some cases, reformed daily trip patterns, mobility, and human behaviors. 
Technological development has provided the basis for the emerg of today’s smart 
cities, which will be a dominant form of tomorrow's cities. In tomorrow's cities, robots 
will be one of the main drivers of urbanization, with revolutionary effects on urban 
transportation systems and providing other services. 
2.4. Cycles of urbanization and counterurbanization 
American geographers have defined the concept of counterurbanization for the 
first time. Considering capitalism, they have conceptualized this theory to study 
the general socioeconomic aspects of urbanization at the regional and national 
levels (Vartiainen, 1989). Counterurbanization means the deconcentration of the 
population from agglomerated urban zones towards urban peripheries or rural 
areas (Dematteis, 1986). In her study on "Making Sense of Counterurbanization," 
Clare Mitchell defined Counterurbanization as a contemporary phenomenon 
25 
 
resulting from changes in social-physical preferences between space and place 
(T.G. Nefedova, N.E. Pokrovskii, A.I. Treivish, 2016).  
In general, counterurbanization has four phases as follows (Figure 17).  
1- Urbanization 2, suburbanization 3, Counterurbanization 4, reurbanization 
The first phase is "urbanization," which is defined as a concentration of population 
in the city centers. In this phase, the direction of the population is from urban fringes 
or non-urbanized zones into the official borders of cities (Marc Antrop, 2004). 
 
Figure 17 Modelling the phases of urban development. Meaning of the abbreviations: – A, absolute; R, relative; C, 
centralization; D, decentralization (Paddison, 2001) 
 
The second phase is "suburbanization," and in this phase, cities will face rapid 
population growth due to the overflow of the migration from the inside of cities' 
official borders towards urban edges and, finally, emerge of suburbans. Today's urban 
inner-zone issues are the main reasons that have forced people to live in the suburbs. 
The development of urban infrastructures and transportation systems has facilitated 
suburbans’ accessibility to travel to other urban zones easier and faster (Matthiessen, 
2013). 
26 
 
The third phase is "Counterurbanization," and cities will face a decrease in the 
size of population and people will move from the inside of cities toward non-
urbanized areas (Antrop, 2004). Actually, it implies demographical and social-
economic deconcentration (Corey, 2013). This phase has two main aspects as follow: 
(a) physical expansion of suburban zones, (b) moving from urban to rural areas 
because of change of human needs and finding new places to meet their needs (T.G. 
Nefedova, N.E. Pokrovskii, A.I. Treivish, 2016).  
Given researchers, in general, counterurbanization happened in regions that have 
experienced suburbanization (Antrop, 2004), (Vittorio Gargiulo Morelli, Kostas 
Rontos, Luca Salvati, 2014). These processes of urbanization, suburbanization, and 
counterurbanization have a cyclical process, which semas to be as a form of 
differential urbanization (Tiit Tammaru, Hill Kulu, Inga Kask, 2013). But regarding 
this thesis, based on the report of the United Nations (see Figure 16), today more than 
50% of the world’s population is living in urban areas, which will be more in the 
following decades. 
27 
 
 
Figure 18 Temporal Characterization of Differential Urbanization (Hermanus S. Geyer, Thomas Kontuly, 1993). 
28 
 
 
Figure 19 The conceptual model of the Phases of Differential Urbanization: Mainstream and Sub-stream Movements 
(Hermanus S. Geyer, Thomas Kontuly, 1993). 
 
Coclirane and Vining (1988) in their study have argued that in the 
counterurbanization phase, according to the acceleration of changes between the core 
and periphery areas, the time to mobilize everything to face reurbanization is short 
(Hermanus S. Geyer, Thomas Kontuly, 1993). Also, the results of Klaassen and Van 
den Berg’s study on European cities development have shown that each phase of 
cities’ development is specified by a particular spatial pattern of shrinkage in cities’ 
core or growth in other rings, including suburban. Also, they have argued, 
29 
 
suburbanization happened between the decades 1950-1960, while in some European 
countries, happened counterurbanization between the 1970s and 1980s (Manisha Jain, 
Stefan Siedentop, Hannes Taubenböck, Sridharan Namperumal, 2013 ). Moreover, 
Dematteis, in 1986, argued that the following main factors have accelerated 
counterurbanization in Italy: 1) socio-cultural and historical backgrounds 2) housing 
market, 3) developing industrial activities in urban peripheries and deindustrializing 
urban zones with many factories that were placed inside of cities’ official borders. He 
argued that the new spatial structures are the results of the counterurbanization and 
conflicts between dominated forms and forces (Giuseppe Dematteis, 1986).  
The fourth phase is named "reurbanization" and in this phase, the direction of the 
population is from the outside towards the inside of cities’ official borders (Antrop, 
2004).  
2.5. Continental urbanization  
Implementation, Experiences, and Outcomes 
2.5.1. Urbanization in Europa 
Historically, pillars of today's urbanization in Europe were founded in Southeast 
Europe in 700 B.C. and slowly has been developed throughout this continent (Marc 
Antrop, 2004). Urbanization is closely related to political structures, economic 
development, and industrial progress in this continent. About two hundred years ago, 
happened industrialization in West Europe, and consequently pushed millions of 
people from rural to cities and triggered rapid urbanization (Michael Wegener, Klaus 
R. Kunzmann, 1993). Industrialization has accelerated the construction of new 
industries and transportation facilities. This economic transition caused significant 
changes in social structures and spatial forms and urban growth (Gotham K. , 2012). 
2.5.2. Urbanization in North America 
Between 1880 and 1929, the industrialization has progressed urban growth in the 
United States Figure 20. During this time, cities‘ buildings became bigger and higher 
(Gotham K. F., 2012), because of the agglomeration of capital, population, proximity, 
nearest accessibility to the resources, and economic growth (Rees, 2016). 
30 
 
 
Figure 20 Pioneer mass-builder Fritz Burns developed Westchester in the late 1930s, devising many of the mass-
production techniques adopted by postwar suburban builders through the United States (Becky Nicolaides, Andrew Wiese, 
2017). 
 
 
Figure 21 The population of urban areas in the United States, 1790-2021 (Leah Platt Boustan, Devin Bunten, Owen 
Hearey, 2013). 
 
31 
 
 
Figure 22 U.S. urban rent premium, 1918-2010. It represents the premium nationally for households of industrial 
workers living in cities (Leah Platt Boustan, Devin Bunten, Owen Hearey, 2013). 
 
In the United States, the rapid urbanization happened during the early period of 
industrial development (Gotham K. , 2012). Between the decades 1929-1941, the 
economic downturn in addition to the first and second world wars forced many 
Americans out of work. And these issues negatively affected welfare, income, 
economic activities, and urban development (see Figure 22) (Lesh, 2000). But later, 
growth in the economic activities had progressed cities’ economic activites, and 
finally resulted to urban growth. This fact shows a significant relationship between 
economic growth and urban growth. Also it should be noted that, the growth of 
industrial activities, particularly in the car industries has promoted suburbanization. 
Because it enabled people to use private cars for daily transport especially after the 
1960s (see Figure 23) (Leah Platt Boustan, Devin Bunten, and Owen Hearey, 2013). 
 
32 
 
 
Figure 23 Irvine, California, exemplified the massive scale of suburban developments after 1960 and their multiple 
functions including suburban housing, offices, retail, and industry. Irvine housed more than 60,000 people by 1980 and 
212,000 by 2010 (Becky Nicolaides, Andrew Wiese, 2017). 
2.5.3. In the Latin American countries 
As was explained before, the industrial revolution and its role in the economic 
growth and developing cities is one of the main reasons of the rapid urbanization in 
the industrialized countries. But this process was not the same for cities in Latin 
America. The form, design, infrastructures, social and economic condition of this 
continent is very different from other continents, and most of the considerable social-
economic changes have occurred since 1950 Figure 24. 
 
Figure 24 Urbanization in the Latin American countries (BBVA, 2017) 
33 
 
The historical backgrounds of political and economic conditions and structures, 
natural resources and environmental limitations, and even socio-cultural are the main 
factors that have created different urban landscapes and growth in any country. As 
shown in the graphs (see Figure 24 and Figure 25), there is a significant relationship 
between urbanization and economic growth.  
 
 
Figure 25 GDP of South American countries per capita, from 1950 to 2016 (United Nations, World Urbanization 
Prospects: The 2018 Revision, 2018) 
In the industrialized countries of Western Europe, the rate of employment in the 
manufacturing and the services sectors is more than Latin America countries (Julia J. 
Henderson, 1957 ). In Latin America, urban population growth resulted from 
expanding services and not industrial development (Harley L. Browning, 1958 ). Also 
urban-rural migration is one of the main factors. For example, in the capital of 
Venezuela, about 47.8 percent of the urban population was born outside the city, about 
44.1in the Federal District of Mexico, and about 51.4 percent in Peru (Kingsley Davis, 
Ana Casis, 1946). 
2.5.4. Urbanization in Africa 
The process of urbanization was in each continent different also in Africa, but not 
in the population changes. The urban-rural migration and increasing urban population 
were the same changes that happened in all continents. According to the statistical 
data, about 43,8% of Africa's population live in urban areas. In the next two decades, 
Africa's urban population will increase "annually" by 3.1 percent, while the rate of 
34 
 
world average annual growth is 1.7 percent (Nations, 2021) (Daniel Hoornweg, Mila 
Freire, 2013). Africa's urban population has been grown from 32 million in 1950 to 
over 587 million in 2021 (Nations, 2021). Moreover, expected it will be double in the 
next two decades and will be more than 1.3 billion in 2050. If these predictions 
become true, it will be one of the fastest urbanization growth that the world will be 
experienced (Turok, 2016). 
 
Figure 26 Urbanization in African (1950-2050) (Daniel Hoornweg, Mila Freire, 2013). 
 
The African cities in the south of the Sahara and Western Nigeria have been 
constructed during the last decades and have new distinctive tissues than other areas 
(Tingwei, 1988). Also, most Europeans live in these areas, so considerable ownership 
differences exist between Africans and the non-African population (Daniel Hoornweg, 
Mila Freire, 2013). The population size in these cities is often unstable because male 
workers work there for limited periods and then return to their tribes (Julia J. 
Henderson, 1957 ). 
In Africa, the migration of low-income families has accelerated the rapid 
urbanization (Alexandra Hill, Christian Lindne, 2010). By 2030, about 350 million 
people will live in African cities (Adesoji David JIBOYE, 2011). Uncontrolled 
35 
 
population growth has faced cities with many challenges in managing and controlling 
transportation systems, water and wastewater, solid waste, and energy (Daniel 
Hoornweg, Mila Freire, 2013) (Turok, 2016). 
2.5.5. Urbanization in Asia 
Over the last few decades, happened some enormous demographic changes in Asia. 
In 1990 the Asia-Pacific had an urban population of just over 1 billion. But two 
decades later the population had grown to 1.76 billion, and it is projected to increase 
to 2.6 billion by 2030 (Mary Jane Ortega, Stephani Widorini, 2018) (UN, 2011). This 
global trend led to the growth of megacities, which have more than 10 million 
populations. But, it should be noted that, half of htem are in Asia (UN Habitat, 2012). 
Uncontrolled urban-rural migration is one of the main reasons for rapid 
urbanization in Asia (Julia J. Henderson, 1957 ) (Hoselitz, 1957). But this process 
became faster by political forces. A high degree of the concentration of political 
centers and organizations in cities, has accelerated the social-economic development 
of cities than rural.  
More than 40 percent of Asia's urban dwellers live in low-quality houses and 
poverty is defined by the following considerations:  
 Shortages in providing essential services 
 Difficulties in access to adequate and secure shelter resulting in health and 
environmental issues.  
 Increased environmental vulnerabilities and natural disasters (UN Habitat, 
2012).  
According to the studies, globalization has also accelerated the economic growth of 
some Asian cities and provided a large market and opportunities (Tinker, 2006). The 
combination of global markets with cheap labor in Asia has accelerated urban-rural 
migration and these cities have become the 'factory of the world.' Producing high-
value-added goods and has developed Asian cities’ economic growth and domestic 
markets (Sheppard, 2014). 
36 
 
2.6. Sustainable urbanization  
The concept of sustainability or sustainable development was employed for the first 
time at the Stockholm conference. The principles of urban sustainability are like 
supportive guidelines for developing cities considering environmental limitations and 
natural potential. Sustainable urban development policies should be developed 
concerning the following aspects: 
 Improving life quality 
 Increasing participation between stakeholders and people 
 Providing long-term solutions  
 Reducing pressures on the environment (Raffaele Lafortezza, Giovanni Sanesi, 
2019), (J. Jorge Ochoa and Yongtao Tan and Queena K. Qian and Liyin Shen 
and Eduardo López Moreno, 2018). 
Attention to the above mentioned aspects helps to provide a multi-dimensional 
framework for developing sustainable urban development policies (in-hai Lu, Shan-
gan Ke, 2018). But for this aim, political and institutional support are needed locally 
and globally. Without political supports, there is no way to solve today’s global crises 
such as climate change, air pollution, traffic, and reducing consumption of fossil fuels 
(an Zhang, Jiapeng Xu, Yizhu Zhang, Jing Wang, Siyu He, Xiao Zhou, 2020). For 
example in this regard, United Nations provided the Sustainable Cities Program 
(SCP). And in this program was paid significant attentions on public participation 
(United Nations, 2021), to create awareness and mobilize local governments (Roy, 
2009).  
2.6.1. Toward a sustainable urbanized world 
The current non-controlled urban-rural migration has progressed a massive 
urbanization globally (Ichimura, 2003). Urbanization is not just the result of economic 
development. So, for developing principles of urban sustainability, should be 
considered the economic, social, and environmental matters. Because it helps to 
maximize the advantages of urban growth for social development (United Nations, 
World Urbanization Prospects: The 2018 Revision, 2018), (Shaheen L. , 2006). Urban 
37 
 
sustainability principles help to maintain the ecosystems, control urban-rural 
migration, reuse or recycle wastes, manage urban growth, optimize land consumption, 
etc. (Suzanne Vallance, Harvey Perkins, 2010).  
 
Figure 27 Share of the urban population globally (UNCTAD, 2018) 
 
 
Figure 28 This figure shows the projections of the world’s urban population ((EEA), European Environment Agency, 
2014) 
38 
 
The World Urban Populations by Region
4000
3500
3000
2500
2000
1500
1000
500
0
Sub- Latin Middle East
Europe & East Asia & North
Saharan America & & North South Asia
Central Asia Pacific America
Africa Caribbean Africa
1970 2951,43447 1521,97611 1822,103543 1760,940471 845,4226659 175,378896 258,022
1980 3229,24019 1828,680928 2025,918241 1927,656864 942,7450269 209,80086 261,057
1990 3397,054963 2132,496295 2212,341323 2114,301513 1022,782192 237,9697271 265,555
2000 3478,235481 2307,45974 2353,44518 2233,156894 1064,907015 266,0128628 271,506
2010 3609,419708 2474,966896 2478,041349 2353,645519 1125,179608 302,3313685 275,351
2017 3697,068287 2575,93562 2562,996094 2430,41757 1164,158095 327,9042752 277,784
 
Figure 29 The urban population of the world by region, 1970-2017 (Create by Author) and (Data by (worldbank, 2018)) 
 
East Asia &
Pacific
4000
Sub-Saharan 3000 Europe & Central
Africa Asia 1970
2000
1980
1000
1990
0
Latin America & 2000
South Asia
Caribbean 2010
2017
Middle East &
North America
North Africa
 
Figure 30 The Radar chart of the urban population of the world by Region (Create by Author) and (Data by (worldbank, 
2018)) 
 
2.6.2. Urbanization and urban land use sustainability 
Generally, today's cities have been grown unsustainably (Weingaertner, 2005), 
(T.V. Ramachandra, Bharath H. Aithal, 2013); otherwise, the world would not face 
such global environmental issues. Most part of the designed urban development 
39 
 
Milion
policies since the 1950s resulted in today's non-sustainable cities and have changed 
natural landscapes into buildings, streets, and urban infrastructure dramatically. For 
example, non-sustainable and rapid urban growth policies and paying attention to 
cities more than rural are the result of uncontrolled urban-rural migration, which has 
progressed land-use changes (Yuzhe Wu a, Xiaoling Zhang, Liyin Shen, 2011), (Hai 
Minh Phama, Yasushi Yamaguchi, Thanh Quang Bui, 2011). So, it is necessary to 
provide new ways to adapt development policies concerning environmental 
limitations, global issues, and increasing public participation (Chengdong Wang, 
Yutao Wang, Renqing Wang, Peiming Zheng, 2018), (Yehua Dennis Wei, Xinyue Ye 
, 2014). Because global commitments and international corporations are needed for 
solving global issues.  
2.6.3. Urbanization and economic development 
The link between economic development and urbanization is undeniable (Tie-Ying 
Liu, Chi Wei Su, Xu-Zhao Jiang , 2015), which has also strongly progressed 
urbanization particularly since the 1900s (Gordon McGranahan, George Martine, 
2012) (Luisito Bertinelli, Duncan Black, 2004). Furthermore, the author believes that 
economic growth, industrialization, and globalization have been the fundamental 
driving forces of today’s urbanization (Peilei Fan, Zutao Ouyang, Dinh Duong 
Nguyen, Thi Thuy Hang Nguyen, Hogeun Park, Jiquan Chen, 2019), (Ronald 
L.Moomaw, Ali M.Shatter, 1996). 
Studies have shown that, the relative growth in demand increases the relative 
importance of the manufacturing and service sectors, particularly in urban areas. 
Since, in general, for constructing these activities is not needed to hectares of land 
parcels; thus, these firms and service centers can be constructed in urban areas without 
remarkable difficulties. For example, you can have just one product in thousand 
hectares of farmland but more than two hundred activities and thousands of services in 
just ten hectares. So, if we argue that, rapid urbanization is associated with faster 
economic growth. Thus, this can not be an exaggeration if we say, the agglomeration 
of big cities' capital has a close relationship to the population growth of cities. 
40 
 
For example, Megeri and Kengnal, in their research using Human Development 
Index (HDI), have studied twenty-two states of India, and according to the results 
economic development has progressed urbanization (M. N. Megeri, Prakash Kengnal, 
2016), (Massimiliano Calì, 2008), (Julia J. Henderson, 1957 ). In their studies, 
economists like Karl Marx and Friedrich Engels, Max Weber, and Georg Simmel 
recognized the role of cities in the emergence and growth of capitalism and cities as a 
center of political and economic power. Max Weber (1958) considered medieval 
European cities and their institutions as fundamental factors for economic 
development and capitalism. For Weber, a city represents a concentrated form of 
formal structures and he emphasizes on harmony, efficiency, and provides 
possibilities for predicting social relations and activities (Gotham K. F., 2012). 
Economists like planners believe that urban growth in developing countries is 
uncontrolled. Such rapid urbanization results from political forces and sectoral 
development policies, which have created polarized and non-developed landscapes. 
Indeed, they describe the situation as urbanization without development. Developing 
countries today are more urbanized than countries at similar levels of development in 
the last century (Ronald L.Moomaw, Ali M.Shatter, 1996). 
 
41 
 
 
 
 
 
 
 
Chapter Three 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
42 
 
 
 
Sustainable Development 
 
 
3.1. Sustainable development 
Since the last decades, the United Nations held many conferences and international 
summits in different countries, such as Stockholm, Brundtland, Rio, and 
Johannesburg, to draw public attention to the main problems that threaten humans and 
the environment. Today’s concept of sustainable development has been developed 
after a long time of international cooperation and many universal summits because of 
many local and global environmental and social-economic issues (Murphy, 2012). In 
the beginning, the concept of sustainable development was employed to draw global 
attention to environmental issues, global warming, climate changes, mobilizing 
communities and governments to control this non-sustainable process, improving 
health services, and reducing poverty (Soltesz, 2008), (Je!rey C. Bridge, A.E. Lulo, 
1999), (Drakakis-Smith, 1995). But during the last decades tried to use this concept in 
many field of science (Ghalam, 2013), and it helped to link the social, environmental, 
cultural, and economic together for making common sustainable policies for our 
common future (Dan Cristian Durana, Alin Artenea Luminita Maria Gogana, Vasile 
Durana, 2015).  
3.2. The emergence of sustainable development theory 
3.2.1. Stockholm conference 3 
Given the increasing environmental and health issues because of rapid industrial 
and urban development,  the general assembly of the United Nations held an 
                                              
3 United Nations Conference on the Human Environment (UNCHE) 
43 
 
international conference (1972) on “Human Environment” in Stockholm (Handl, 
2012). The main axes of the conference were defined as follows: 
1) A declaration and action plan for global health issues in developing and 
developed countries (ET Sullivan. Ind. L. Rev., 1972) 
2) Making some practical solutions and inviting all countries to participate in an 
international action plan (United Nations, Report of the United Nations Conference on 
Human Environment, United Nations Conference on the Human Environment 
(Stockholm Conference), 1972). 
In this conference‘s report was emphasized on supporting local governments during 
the making and implementing local development policies and projects to enhance the 
quality of life and contribute to a sustainable form of economic growth (Martin W. 
Holdgate, Mohammed Kassas, Gilbert F. Whithe, 1982), (Kennet, 1972), (Emmelin, 
1972). 
3.2.2. Brundtland commission 4 
Brundtland World Commission held in 1984 by United Nations on “Environment 
and Development” and 900 days after the conference, was published a report under 
the title “our common future” in 1987 (Emas, 2012). This commission had defined the 
first definition of “Sustainable Development” as follows: It is a new form and path of 
development that meets the needs of the present generation without depletion of 
natural resource capacities and abilities (McManus, 2014). Sustainable development is 
like development with “responsibility” and efficient use of renewable and non-
renewable resources concerning social and environmental limitations (Keeble, 1987), 
(Redclift, 1989).  
Another definition provided by the Britannia government on “Sustainable Society,” 
refers to the places where people decide to be there for living and working (Downing, 
Andrea S; Chang, Manqi; Kuiper, Jan J; Campenni, Marco; Häyhä, Tiina; et al. , 
2020). Indeed living and working are two main keywords in this definition that 
                                              
4 World Commission on Environment and Development (WCED) 
44 
 
survival of both parts are dependent on human and environment sustainability because 
human’s life and activities are tied to the sustainability of the environment. 
Sustainable development means rearrangement of technical, practical, environmental 
capacities with economic and social development policies to realize sustainability. 
Also, this commission paid attention to the necessity of education in the 
development of the social sector to increase social capacities (Muñoz, 2020), and 
public participation in waste management or recycling (Borowy, 2013), (M.Harris, 
2000). For example, people can significantly encourage factories to use recyclable 
materials for products by declining to buy products packed in non-recyclable material. 
But at that time, some people criticized that the defined goals and policies are more 
general and should be more detailed considering different local conditions (Næss, 
2007), (Borowy, The Brundtland Commission:Sustainable development as health 
issue, 2013) (Pearce, David, and Giles Atkinson, 1998). In contrast, supporters argued 
that local policies have to be designed by local governments considering their own 
local conditions (Alpopi C., Manole C.. and Colesca S. E., 2011).  
3.2.2.1. The main aspects of Brundtland’s report 
These aspects were classified into different groups considering type and role as 
follows: 
a) Promoting healthcare  
b) Supporting poor and homeless people 
c) Increasing the ability of low-income groups to improve living conditions 
d) Monitoring and decreasing environmental degradations,  
e) Developing new energy resources to decrease the consumption of fossil 
fuels (ChrisSneddon, Richard B.Howarth,Richard B.Norgaard, 2006), 
(Burton, 1987 ). 
45 
 
3.2.2.2. The main dimensions of sustainable development in the 
Brundtland’s report 
According to the report, the main dimensions of the Brundtland report are: 
environmental sustainability, economic sustainability, and social sustainability, 
physical and political sustainability  (Auty, 1997), (Bass, 2007). 
3.2.2.2.1. The objectives of environmental sustainability: 
 Identifying environmental limitations, potentials, and capacities, 
 Identifying and minimizing the adverse effects of artificial phenomena on the 
environment, 
 Management of natural resources efficiently, and avoid depletion of the non-
renewable and valuable natural resources just for short-term goals or private 
interests of some particular groups (Ralf Barkemeyer, 2011). 
3.2.2.2.2. The objectives of economic sustainability: 
 Progressing sustainable development by identifying new economic potentials 
 Promoting principles of sustainable development in all economic development 
policies 
 Promoting sustainable development patterns at the local, national and global 
levels 
 Increasing the efficiency of goods and services 
 Maximizing efficient use of mineral resources (David Pearce, 1998). 
3.2.2.2.3. The objectives of social sustainability: 
 Increasing the quality of life in terms of welfare, social quality, and sharing 
development costs and benefits equally 
 Equal access to healthcare services 
 Providing new legal mechanisms for making sustainable development policies 
(Paul, 2008). 
3.2.2.2.4. The objectives of physical and political sustainability: 
 Identifying potentials of human and natural resources and capacity building 
to establish viable settlements to support low-income families (McChesney, 
1991). 
46 
 
 Strengthening democracy and increasing participation of people in the 
decision-making process through the empowerment of the local community 
(Newman, 2006).  
3.2.3. Earth summit 
This conference organized by United Nations on “Environment and Development” 
in 1992, Rio de Janerio, Brazil. The conference followed the former conferences and 
with the cooperation of most countries to promote sustainable development policies 
globally. And after the conference, United Nations had published this conference‘s 
report with the title “Agenda 21” (Jane A. Leggett, Nicole T. Carter, 2012). This 
report included commitments, recommendations, guidelines, and providing financial 
resources to accelerate sustainable development. Agenda 21 was published in four 
chapters considering the following sectors: 1- social and economic sectors, 2- 
management of human and natural resources, 3- strengthening communities and 
NGOs (Panjabi, 1997), (Sitarz, 1993).  
The conference promoted making new policies and developing land-use models to 
reduce non-sustainable land consumption and improve land management for 
decreasing pressures on urban lands (Jr., 2015), (Davidson, 2006), (Kiernan, 1992). In 
this report, “land” is defined as an unrenewable and valuable resource (Palmer, 1992), 
(Grubb, M., Koch, M., Thomson, K., Sullivan, F., & Munson, A, 2019). 
3.2.4. Johannesburg summit 
Johannesburg Summit was an international conference on “Sustainable 
Development” and was organized by United Nations with the cooperation of most 
countries in 2002, in Johannesburg, South Africa. The conference followed the former 
conferences but thematically had focused particularly on sustainable development 
(Frantzius, 2004 ). The final report of the Johannesburg included commitments, 
responsibilities, and cooperation generally (Speth, 2003 ). This conference promoted 
the integration of development policies for the following sectors: “economic 
development, social development, and environmental development. Also as 
mentioned in this report, governments, organizations, private sectors, and people are 
responsible for this process (Gill Seyfang, 2002). Globalization was also another main 
47 
 
topic that was discussed at this conference (Nath, 2003). Globalization has provided 
new opportunities and challenges for trade, investment, and capital trends. Therefore, 
this conference suggested making new policies to arrange and manage connections 
and activities among countries and develop regional partnerships via cooperation. 
3.3. Urban sustainability 
As we know, up to 2030, about 60 percent of the world's population will be settled 
in urban areas (Song, 2022), (The Role of Cities in Sustainable Development, 2010). 
Increasing migrations towards cities are one of the main reasons that have accelerated 
urbanization and urban physical growth (Anne Shepherd, Leonard Ortolano, 1996), 
(Mostafa Rasoolimanesh, Nurwati Badarulzaman, Mastura Jaafar, 2011). Even this 
issue, with different negative consequences depending on local conditions, is 
becoming more complicated in developing countries (Dr. Ayman Nour Afify, 2002). 
Thus, the ability of cities to implement sustainable development policies considering 
the spatial-time would be different. For example, most of the urban problems in 
developed countries are concentrated on reducing the consumption of fossil oil to 
control climate change and global warming. But in developing countries social and 
health issues are prior to environmental issues. Researchers believe that, sustainable 
urban development is related to equality, social justice, fulfilling basic human needs, 
as well as attention to employment, poverty, health, urban physical environment, and 
infrastructures (Steven Curwell, Mark Deakin, Mark Deakin, 2005). 
 
 
 
 
48 
 
 
 
 
 
 
 
Chapter Four 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
49 
 
 
 
 
Urban sprawl growth and land 
use changes 
 
 
 
4.1. Urban growth 
City growth emerges as spatial and physical changes resulting from the 
concentration of population in a place because of social-economic or environmental 
potentials. Generally, urban growth considering geographical and spatial 
differentiation can be different. The intensity of urban growth and physical expansion 
will be affected by the factors of time, forces, tempo, and scale of changes in the 
economic, social, and demographic sectors.  
Since the last century, changes in the physical structure and nature of cities were 
accompanied by changes in urban functions, land use and the emergence of new 
activities in cities. Changing natural resources like raw lands into numerous buildings 
with commercial, residential, industrial, and service functions have occurred under the 
daily growth of a big factory that we have constructed and named "City." As well, 
today’s urban daily life challenges and issues became more complex. Some significant 
forces such as economic policies, dominated ideologies, planning culture, and local 
specific conditions and potentials have played substantial roles in accelerating or 
decelerating peace of urban growth and development and generating new spatial 
landscapes locally and globally (WÄLTI, 2004). For example, the industrial 
50 
 
revolution and free market policies of the industrialized countries have constructed a 
new spatial organization of the market and escalated environmental problems such as 
climate change globally. In this regard, according to the Paris climate agreement, one-
hundred and eighty-seven countries were committed to reducing environmental 
emissions. Still, the most producers of emissions are industrialized countries 
including: China, the USA, European countries, Japan, and also developing countries 
including Brazil, India, Russia, Canada, Indonesia, South Korea, Mexico, Saudi 
Arabia, and South Africa (Schreurs, 2016), (MichailFragkias, Christopher GBoone, 
2016 ). 
 
 
Figure 31 Share of greenhouse gas emissions by countries (Schmidt, 2015). 
 
Perhaps the declining disadvantages of urbanization to reduce consumption of non-
renewable resources such as urban lands are one of the main reasons. According to 
this study, increasing investments in new technologies to reduce the consumption of 
natural resources and fossil fuels can effectively decrease urbanization's 
disadvantages. For example, tiny mobile houses are the new generation of home 
building that have enabled people to be mobile and transport their homes and this 
creative design has reduced the consumption of land parcels. 
51 
 
4.2. Criteria of urban changes concerning the urban 
environment 
A city functionally is as a centralized factory that includes people, buildings, needs, 
production, consumption, interactions, and transportation as inputs. So, workers, land, 
capital, technology, and natural resources are required forces in the growing process 
of a city. This thesis believes that, identifying the main forces of urban changes and 
analyzing the scale and pace of these changes in the formation of artificial 
environments is crucial in urban studies. It helps to find the reasons of the current non-
sustainable urban development and providing effective solutions for today's urban 
challenges. Because the interaction and link between urban issues are multi-levels and 
became complicated with many internal and external factors. It means there are many 
reasons just for one problem and one change in a city. And any change can be a reason 
for emerging new changes or issues. And they are constantly circling from one space 
to another space and changing from one form to another form Figure 33.  
Generally, the following forces have accelerated urban changes:  
A) The factor of place as a base that has provided the possibility for constructing 
and promoting a multi-level interaction between places 
B) The factor of natural resources that helped to fulfill the needs and promoted 
welfare 
C) Shelters (house or apartment) functionally are a place that meets human 
material needs, (survival needs), spiritual needs (about the soul and intellect), and 
reconsidering the urban dwellers as a consumer of goods and services. 
So, this thesis emphasizes finding new sustainable and renewable building 
materials to control rapid urban land use changes and reduce environmental tensions 
created by human activities. In this regard, in the early 21st century, UNESCAP5 
suggested the "Green Growth" theory to support cities and realize compatibility 
between human settlements and green areas and to promote low‐carbon cities 
                                              
5 The United Nations Economic and Social Commission for Asia and the Pacific 
52 
 
(UNESCAP, 2011). For example, Resnick and colleagues (1990) have studied the 
relationship between economic forces and green growth policies and found out the 
main roles of economic forces in reforming and creating urban spaces. The growth of 
economic activities in lower-developed urban zones has increased the green building 
projects in these zones significantly (Danielle Resnick, Finn Tarp, James Thurlow, 
2012). Also the results of the other study on the effects of economic activities on 
urban structure have shown that, in some urban zones with less financial growth, the 
quality and quantity of economic activities, diversity of landuses, attractivity, and 
landscapes are significantly inadequate and insufficient. Therefore, they have 
proposed establishing new services, facilities, technological infrastructures, and 
developing social skills are required for the development of these zones 
(TinglinZhang, Bindong Sun, Wan Li, 2017). Christopherson, in a study, has revealed 
that changes in economic interactions, production, and spatial division of labor market 
are the main reasons to reconstruct or arrange urban spaces, determine the land-use 
type, and change the urban spaces (Christopherson, 1989). 
Further to the local economy, the global market plays a significant role in 
organizing urban spaces. Globalization expanded the free market and linked local 
markets to the global and specially developed urban economy and accelerated urban 
changes (Gordon, 1995). International economic forces have rearranged spatial 
patterns activities, deciding where to build up a factory and, of course, job market. 
The intensity of changes in the urban spatial organization depends on the 
concentration and densification of economic activities concerning a city's local 
potentials and social-economic characteristics  (Mingxing Chen, Hua Zhang, Weidong 
Liu, Wenzhong Zhang, 2014). Thus, control of both natural and human spaces without 
control of the market would be challenging. In this regard, the green growth approach 
tries to consider social and environmental concerns in the economic development 
policies to realize urban and environmental sustainability faster (UNESCAP, 2011). 
 
 
53 
 
Spatial 
places
valuable 
natural Shelters
resources 
Urban 
Developemnt
 
 Figure 32 significant forces that participate in the urban development (by the author) 
 
 
Figure 33 Urban frames, layers, and the formation of urban spaces and structures (by the author) 
54 
 
Green Growth 
theory
Redirection of Protecting 
policies, both artificial 
planning and and natural 
architecture environments
 
Figure 34 The three main pillars of the Green Growth theory (by the author) 
 
4.3. Changing urban environment under social changes 
Change in the social and cultural sectors can change social behaviors to control 
urban changes. For example, changing demographic control policies from one-child 
culture to the two or three-child consequently increases demand for new and bigger 
buildings, increases demands for new land parcels, and increases the construction of 
new infrastructures (Fong, 2002). As a result, emerges new changes in urban space, 
structure, activities, and land use are conceivable. In the land uses planning and 
locating practice, attention to principles of the green growth theory helps to establish 
compatible structural linkages among people, land parcels, and activities Figure 35. 
As shown in Figure 35, the pattern one -increases the costs of time and transport, -
increases traffic and consumption of fossil fuels, and -increases air and sound 
pollution than the pattern two. The first pattern encourages using private cars instead 
of using trains or buses. However, the second pattern provides a shorter way to go to 
work or other activities and encourages walking or using bikes. 
55 
 
 
Figure 35, intracity transport patterns (by the author) 
 
 
  Figure 36 Major factors with significant roles in the sustainability area (Brand, 2005) 
 
According to Hall and Peiffer, new social values and internal or external factors 
affect lifestyle, activities, and mobility patterns in an urban space. These novel 
changes later can generate new urban special-physical landscapes. Change in social-
cultural values directly affects the household size and influences public tendency even 
to be single or childless, which happened in the industrialized countries. Studies have 
shown the rise of childlessness, and more adults do not have children in European 
cities (Gottdiener, 1994). For example, since 2005, the POCKET LIVING Company 
build and sell small flats in London. These apartments have many required spaces for 
young or single people, such as bicycle storage, and lack the things they do not, such 
56 
 
as large kitchens and lots of bookshelves. At first, Pocket has expected that most 
buyers would be in their late 20s. Instead, the average age is 32 and rising. It is not 
that many purchasers are yet to have children; rather, they perhaps will never have 
them (Corfe, 2019). 
The growing European urban population are in the same situation. 9% of English 
and Welsh women born in 1946 had no children. For the cohort born in 1970—who, 
barring a few late surprises, can be expected to be done with babies—the proportion is 
17%. In Germany, 22% of women reach their early 40s without children; in Hamburg, 
32% do (Economist, 2017). 
This difficulty affects the structure of jobs, wealth state, and rearranges urban 
spaces, land use type, and locating.  
 
 
  Figure 37 Engineering social behavior towards sustainability issues (by the author) 
 
Human behavior and activities are a reflection of social-cultures values. Thus, it is 
possible to embed environmental concerns within social and cultural values to change 
human behavior and finally change spaces. In this sense, between the variables people 
and activities, people are considered as a fixed variable. And activities are regarded as 
a dependent variable and create new spaces.  
57 
 
Hence, given the significant influences of social and cultural values on human 
activities, it is no overstatement if we claim, "social-cultural factors are one of the 
main shapers of artificial spaces." Therefore, for the management and control of urban 
land use, cultural planning and building new values to draw public attention to the 
environmental concerns are required. 
 
Figure 38 engineering social space to reshape environmental space (by the author) 
 
Consequences of land use changes on the quality of urban spaces 
In today’s land use planning, attention to the principles of sustainability is 
necessary for creating new spaces with respect to the type of activities, health issues, 
and environmental limitations (Tulshi Kumar, Rony Basak, 2020). According to the 
studies, allocating land to the public and private green spaces such as parks and 
gardens enhance urban health, decrease sound pollution, and provides a more 
desirable environment, particularly in crowded urban zones with high density (C. Yu, 
2006). Therefore, designing and creating desirable and environmentally friendly 
places increases social interactions and encourage people to walk instead of using a 
car.  
Land use activities affect the physical and mental health of urban dwellers directly 
and indirectly. Different land-use types such as (green space, residential, commercial, 
sport, etc.), single or mixed-use create diverse landscapes. Thus, measuring public 
welfare, physical activity, health, social integration, and ecological matters should be 
considered in land use planning. For example, single or mixed-use land or building 
gives different accessibilities for urban dwellers when they want to go shopping, sport, 
etc. (Byoung-Suk Kweon, Christopher D Ellis, Pedro I Leiva, George O Rogers, 
2010).  
58 
 
 
Figure 39 The influential factors for delivering a better sense of place in the land use planning act (by the author) 
 
4.4. The consequence of population changes on land use 
changes 
Rapid population growth increases dwellers' needs and simultaneously increases 
pressures on the capacities and infrastructures of a city such as urban lands and causes 
many problems (Clark, 1977). Population growth considering the social-economic 
conditions of places will happen rapidly or gradually. Rapid population growth in a 
short time usually results from a massive migration of people from many areas to a 
city. This issue in overcrowded cities faces urban dwellers with unequal access to 
daily services to fulfill their needs (Tine Ningal, A.E. Harteminka, A.K. Bregtc, 
2008). Regarding the United Nations reports, massive increasing urban-rural 
migration since the past century (Berry, 2008), has dramatically changed the form, 
texture, and landscape of cities. The impacts of this trend regarding the local 
conditions from one place to another were different; thus, its effects in some places 
were dramatic and in some places were not remarkable (Jaños P. Hrabovszky, K. 
Miyan, 1987).  
It should be noted that migration and population growth in developing countries for 
example Iran are substantially higher than in developed countries especially since the 
last decades, even it will be more in the following decades (Bilsborrow, Richard E. 
59 
 
Okoth-Ogendo, 1992). The extreme imbalance between the urban and rural 
populations in Iran mainly resulted from unequal development policies, local 
potentials, and polarized growth. New urbanism and change of lifestyle, supporting 
the cities more than the rural area, increasing job opportunities in urban areas than 
rural areas, and growth of consumerism are the main reasons for this uncontrolled 
urban-rural migration. 
4.5. Social equality and land use sustainability 
Unequal development and polarization have escalated social gaps and created 
different urban landscapes as follows: 
1- Settlements without infrastructures for low-income families 
2- Structured settlements for middle and high-income families with more facilities 
and services (Michael C. Lens, Paavo Monkkonen, 2016).  
Generally, in developing countries, low-income families are settled around urban 
edges or suburbs. In contrast, usually in developed countries, low-income groups are 
settled in the center. And middle or high-income groups are settled far away from the 
center (Pepijn Schreinemachers, Prasnee Tipraqsa, 2019), see Figure 40 and Figure 
41. 
  
Figure 40 A planned and infrastructured suburb Figure 41 A slum without basic infrastructures 
(Fettmann, 2019) closed to the developed zone with big-buildings and 
best infrastructures (Villa, 2017) 
Today, high and middle-income groups tend to live in some suburbs to have larger 
houses, gardens and lower sound pollutions. While the majority of low-income 
families living in the slums or informal sectors under inappropriate conditions (Long 
Cheng, Xuewu Chen, Shuo Yang, 2016). This thesis argues that, both forms of land 
60 
 
consumptions are non-sustainable Figure 40 and Figure 41. Maybe new technologies 
and finding new building materials and methods can effectively provide small and 
lightweight constructions for settling people in slums and decreasing consumptions of 
raw land. For example, please look at the following pictures Figure 42 and Figure 43. 
This project resulted from a novel combination of science and industry to offer 
compacted and cozy rental homes in the Netherlands. This project has focused on the 
three main aims: sustainability, efficiency, and minimizing environmental 
degradations, and realize a sustainable linkage between artificial phenomena and 
nature (Davis, 2018). 
 
Figure 42 A conceptual model of Stone-shaped 3D-printed rental homes in the Netherlands (Davis, 2018) 
 
Figure 43 A conceptual model of Stone-shaped 3D-printed rental homes in the Netherlands, by Houben/Van Mierlo 
architects (Davis, 2018) 
According to studies, generally, the informal sectors are settled by low-income 
people (Tarsi, 2020). Because of financial problems, they tend to prepare needed land 
61 
 
parcels by occupying or buying cheaper than the land market price. And then, land 
parcels will be constructed without permits and cheap materials (Meagher, 1995). For 
example, in most Iranian cities, growing informal sectors have increased informal land 
occupations, land consumptions, and also land value. In the year 2019 was done a 
national project in 77 cities of Iran, and planners found about 851 informal sectors in 
about 52443 hectares and with more than 5900,000 population (Armin, 2019). 
Unfortunately, there is no supportive housing plan for low-income families. For 
example, in the Comprehensive Plan, studying the social-economic aspects of cities 
are just limited to writing a short report on cities’ social-economic situation. 
Therefore, an effective social-economic analysis considering the principles of 
sustainability must be provided to improve urban health and support low-income 
groups. Yıldız and colleagues in their study have argued that social equality has a 
close linkage in the realization of social-economic sustainability and environmental 
sustainability (Serkan Yıldız, Serkan Kıvrak, Arzuhan Burcu Gültekin, Gökhan 
Arslan, 2020). As a result, in urban land use planning, attention to the social justice, 
supporting low-income families, making new supportive strategies to settle low-
income families are essential for realizing social-environmental sustainability.  
4.6. The characteristics of suburbans  
In this study, suburb means a residential or mix-used settlement that are placed 
around of a city (Caves, 2004) and includes social, political, environmental, and 
economic characteristics. Suburbs is the result of the continuation of centrifugal 
development (Dembski, Sebastian; Schulze Bäing, Adreas; Sykes, Olivier, 2017). 
Suburbanization has emerged as an uncontrolled trend in American cities by offering 
new desirable private spaces and accessible by car. 
62 
 
 
Figure 44 The conceptual model of developing urban zones (by the author) 
 
The progressive urbanization and emerging new forms of settlements such as 
suburbs and exurbs resulted from drastic social-economic changes, especially since 
the second half of the twentieth century (Murtagh, 2004), (Ivonne Audirac, 
Emmanuèle Cunningham-Sabot, Sylvie Fol, Sergio Torres Moraes, 2012). Moreover, 
European urban planning literature has used "suburb" to describe a disadvantaged area 
that is segregated from a central city. But in the USA, this term don not used to 
describe underprivileged regions. In some references, suburbs or exurbs refer to areas 
that have low-density development (Harris, 2010).  
Infrastructured suburbs with the enough accessibility to service centers have 
progressed suburbanization and motivated people to move from the inside of cities 
towards the outside such as suburbs (Schmidt James W, Arnold Robert K, Levy 
Stephen, 1972). Suburbanization has progressed non-sustainable urban growth and 
transformed valuable natural spaces into built-up zones Figure 40 and Figure 41. 
63 
 
4.7. Urban sprawl growth  
In urban studies the word "urban sprawl" was used for the first time in the year 
1956 ( Gregory D Squires, 2002) (S.Habibi, N.Asadi, 2011), (Gillham, 2002). Sprawl 
growth is an uncontrolled and scattered form of urban physical growth (Frumkin, 
2002). But, any physical growth doesn't mean sprawl growth. A city can also have a 
progressive physical growth but planned and integrated, which will be horizontally or 
vertically considering densities (Thomas J. Nechyba, Randall P. Walsh, 2004). Urban 
sprawl represents a low-density type of land use development, and emerges in 
different forms like ribbon, strip, and leapfrog (Johnson, 2001 ). However, this type of 
growth is non-sustainable and since the last decades created or escalated many 
environmental and social issues (Ottensmann J. R., 1977). 
4.8. Urban density, efficiency and effectivity 
In general, urban density has an effect on social-economic activities (Glaeser, 
2011). Increasing the density of buildings will increase the density of activities and 
population in a place. So, increasing urban density without considering environmental 
and spatial limitations is unsustainable and escalates urban issues. For example, the 
Coronavirus pandemic faced cities with social-economic crises (Jingjing Wang, 
Yiyang Yang, Jiandong Peng, Linchuan Yang, Zhonghua Gou, Yi Lu, 2021). 
Particularly, the places with more density of population, buildings, and activities 
became more vulnerable than other places. Because of more infections, these places 
were faced with more lockdowns than other zones (Gilles Duranton, Diego Puga, 
2020).  
However, sustainable urban design and land use planning decrease the imbalance 
between spaces and activities of land parcels, especially in the agglomerated and high-
density zones. An excellent example of the high density and effective usage of land 
parcels and urban spaces is compact city building. 
64 
 
 
 Figure 45 a sample model of a compact city (Sang-gil, 2018) 
 
A compact city concept promotes mixed-use activities and provides better 
accessibility for people. In the following are mentioned some advantages of this 
concept: 
 promoting mixed-use instead of single-use increases the scale of activities, 
which improves the quality of service to the people 
 developing the capacity of urban spaces and decreasing consumption of raw 
land parcels, 
 providing faster access to the daily service, which reduces the time and 
length of daily trips and decreases the dependency of people on using private 
cars 
 reducing traffic and consumption of fossil fuel 
 reducing air pollutions and improving air quality (Muhammad Zia Mahriyar, 
Jeong Hyun Rhob, 2014), (Nicola Dempsey, Mike Jenks, 2010). 
The compact and high-density building has remarkable economic benefits for cities 
and dwellers. Because, the cost of time and transport will decrease by increasing 
density (Burgess, 2000). In addition, high buildings with more density reduce the cost 
of the establishment of infrastructure (YifanYang, S. Thomas Nga, Frank J.Xu, Martin 
Skitmore, 2018). Since, city building vertically reduces the growth of cities 
65 
 
horizontally, and as a result, the length of transportation infrastructures including 
asphalts, railroads, and bus lines in a compact city are not longer than in other cities. 
Even the cost of gathering garbage in a compacted city is more affordable than in 
cities with sprawl growth Figure 46, Figure 47. 
 
Figure 46 Decreasing the occupation of urban spaces by increasing urban density and High-rise building  (Saleh 
Abdullahi, Biswajeet Pradhan, Abubakr Al-sharif, 2017) 
 
 
Figure 47 Potentials of urban horizontal growth and its effects on the urban activities and land consumption (by the 
author) 
 
66 
 
4.9. Density and optimizing structure and size of cities 
For the first time, the theory of optimal city size was developed to analyse the 
relative between the population and area of a city. But later this term was used to 
analyze the relationship between the efficiency of spaces and the size of cities 
considering economic factors (Yuhong Cheng, 2017). For example, Roberte and 
colleagues were done a study to analyze the size (area) of a city considering the 
following factors: quality of life, economic agglomeration, social tension, and rent of 
land parcels (Roberto Camagni, Roberta Capello, Andrea Caragliu, 2013). Or Yang in 
his study considered social well-being per capita to define the optimal size for a city 
(Yang, 2020). In European urban planning literature, the population is the main factor 
in defining the optimal size of a city (Javier Monclús, Carmen Díez Medina, 2018),  
(Sadowski, 2020 ). Because, the agglomeration of the population has a connection 
with the costs of establishing public services (Peter Nijkamp, Adriaan Perrels, 2014). 
For example, in cities with horizontal growth and low-density development it is 
necessary to have a larger transportation system, but this issue increases the 
consumption of resources (Hadi Arbabi, Martin Mayfield, Philip McCann, 2019). 
Also, Arnott (1979), who is in favor of the compact cities idea, has argued that, the 
concentration of population reduces the cost of production, which is very important 
for sustainable urban Development (Arnott, 1979). Therefore, growth in the area of 
cities increases the costs of service, spatial costs, and disturbs the balance between 
resources and needs, and affects on cities' functions negatively.   
Unfortunately, today's urban policies generally have concentrated on achieving 
economic growth, and this problem imposes many costs to the societies, environment 
and declines the quality of open spaces (Frenkel, 2004). Contemporary urbanization 
has progressed suburbanization and sprawlization growth. And hope that post-
urbanization would control and direct urban growth and development towards 
sustainability locally and globally. Continuing interregional migration towards urban 
areas while most people move from city centers to the periphery or suburbs develops 
multicentric urban systems Figure 47. 
 
67 
 
 
Figure 48 The conceptual pattern of Sprawl growth  (by the author) 
 
According to most empirical studies, sprawl development is quite unsustainable 
and has many disadvantages for the social, economic, and environmental sectors 
compared to the compact model. 
In the contemporary urbanization era, market forces play a significant role in 
changing cities' functions, urban growth, quantities and qualities of land consumption, 
type of activities, and also changing desire of consumers (Amelia F. Darrouzet-Nardi, 
William A. Masters , 2015), (Amanda J. Lea, Dino Martins, Joseph Kamau, Michael 
Gurven, Julien F. Ayroles, 2020). In such a condition, urban land use principles are 
one of the main tools to control the unsustainable use of valuable natural lands by 
market forces. 
4.10. Costs of sprawlization 
Urban sprawl growth and physical expansions, as one of the main negative aspects 
of contemporary urbanization and suburbanization, have imposed social-
environmental costs on the communities and environment (Burchell, R. W., 
Lowenstein, G., Dolphin, W. R., Galley, C. C., Downs, A., Seskin, S., ... & Moore, T., 
2002). Implementing temporary and inappropriate urban policies particularly after the 
second half of the last century have increased the costs of sprawlization. The 
sprawling growth has replaced soft surfaces such as green or open spaces with hard 
68 
 
surfaces like asphalt roads and buildings. Sprawlization destroyed agricultural lands, 
threatened ecosystems, and increased intergenerational inequity. It also led to unequal 
access to natural resources and eventually has diminished the desirability of human 
life and even the quality of the environment. In continue provided some examples to 
show the area of some cities with compact growth in comparison with the cities with 
sprawl growth considering the population and density (see Table 5). 
Table 5 Comprising the cities with sprawl growth versus the cities with compact growth (by the author) 
Sprawling City Compact City 
Total Total 
Population Population 
City Population area City Population area 
density density 
(km2) (km2) 
Ankara 4,470,800 1,910 2,340 Kolkata 4,496,694 185 24,306 
 
 
Cape Town 3,740,026 2,444 1,530 Giza 4,239,988 289 14,667 
 
 
69 
 
Rome 
4,353,738 5,363 812 Cairo 7,601,018 302 25,582 
Capital 
 
 
Shenyang 8,106,171 12,980 625 Seoul 9,806,000 605 16,202 
 
 
Los Angeles 3,976,322 1,213 3,276 Mumbai 12,442,373 437 28,426 
 
 
 
70 
 
Chengdu 9,012,000 14,312 630 Tokyo 13,515,271 626 21,556 
 
 
Alexandria 4,616,625 2,300 2,007 Dhaka 14,399,000 337 42,659 
 
 
 
Sprawlization and uncontrolled growth of cities since the last decades generally 
welcomed most groups of citizens (Robert W. Burchell, David Listokin, Hilary 
Phillips, 1997). As a result, today’s cities have two different landscapes including old 
tissues with more density, and new tissues with lower density of population, activities 
and buildings. Therefore, people don't like more living in the cities' zones with old 
tissues, where threats their health and security (Roman Trubka, Peter Newman, Darren 
Bilsborough, 2010). It should be noted that, the fragmentation of open spaces and 
scattering residential areas increases social-economic inequality (Robert H. Freilich, 
71 
 
Bruce G. Peshoff, 1997). Thus, in addition to the environmental costs, social and 
economic costs are identified as one of the main costs of sprawlization. 
4.10.1. Social costs 
According to studies, the value of land or house in the suburbs are generally higher 
than in other urban zones. Therefore, low-income families have a lower chance to live 
with other social groups together in a place. And this issue led to the polarization, 
increased social gaps, and created new urban spaces based on the income (Bajari, 
Patrick, Matthew E. Kahn, 2004). Therefore, the privatization of places, spatial and 
social segregations progressed urban expansion from the core towards suburbs and 
exurbs. Moreover, Euclidean or single-use zoning and land segregation change social 
behaviors and living conditions (Robert H. Freilich, Bruce G. Peshoff, 1997). 
Reducing the quality of living conditions in the inner cores of cities because of air 
pollution, noise pollution, highly dense population, and traffic motives people to live 
in suburbs  (Gerda R. Wekerle, Paul S. B. Jackson, 2010) (Barros, 2012), (John I 
Carruthers, Gudmundur F Ulfarsson, 2003). This thesis belives that, these issues 
resulted from inefficient urban development policies. If the low-income families are 
accepted to live in the city centers doesn't mean they are satisfied; perhaps this is their 
last alternative to find a temporary shelter. Maybe as soon as they have better living 
conditions they would live in suburbs. In such a chaos condition, maybe participation 
of researchers from different scientific fields such as urban planning, architecture, 
sociologist, politicians, NGOs and people is necessary in decision-making. Because, 
in this new millennium, urban issues became more complex than before. Today's 
urban challenges result from the pure idealism and execution of inappropriate policies.  
Contemporary cities still are not an ideal living place for people. According to the 
relativity of time, local and spatial conditions, human needs and desires change 
over time. And the intensity of these changes depending on the lcoal and spatial 
conditions will be high or low. In this regard, today’ changes of the wishes and needs 
of the current generation in comparison with the past generations in terms of quality 
and quantity have changed public desires and encouraged them to experience new 
places and things. For example changes of values, norms, culture, technologies, 
72 
 
transportation, and economic activities. And these changes distinguish places from 
each other and create places with different landscapes and issues. For example, 
developing urban transportation systems increased urban mobility and enabled people 
to find a job rather far away from where they live. Aa a result, this issue is has 
increased suburbanization, and today's urban management tools are not enough 
effective to settle people within the official border of cities. Thus, accommodation of 
urban planning theories, methods and procedures, design, and management with the 
contemporary urban problems and challenges is inevitable.  
We have to consider that, human needs are endless, and nothing can guarantee to 
keep all people within a city's borders for a long time. In tomorrow's cities, not only 
urban planners, architects, or policy-makers, but all social and scientific groups have 
to be invited in the city planning and building steps. In addition, unfortunately, over 
the past half-century, we have paid more attention to urban economic development 
than urban social and health development. And this issue has driven urban 
development towards non-sustainability.  
This thesis argues that, modernism is the other main factors that has intensified 
urban changes, suburbanization and counterurbanization since the last decades. 
Actually, the modern urbanism was born to correct development policies mistakes of 
industrial cities using the Utopian proposals and new urban planning ideas (Pearlman, 
2000). For example, London, with two development plans including County of 
London Plan (1943) and the Greater London Plan (1944) is a classic model of 
modernity that were provided by Patrick Abercrombie and his team. In both plans, 
designs of new residential areas were committed to a functional approach, and despite 
criticism were widely imposed to be implemented (Abercrombie, 1912), (Patrick 
Abercrombie, 1943). The other example is Europe's mass housing estate policy 
between the 1960s and 1970s and this policy is the result of the International 
Congresses of Modern Architecture or (CIAM6) (Miles Glendinning, 2019). This 
                                              
6 Congrès Internationaux d’Architecture Moderne (CIAM) or International 
Congresses of Modern Architecture 
73 
 
policy was designed to solve the shortage of housing quickly, but led to the rapid 
urban growth (Javier Monclús, 2016) (Javier Monclús, Carmen Díez Medina, 2018). 
The other forces is technological urbanism that appeared as an alternative to 
traditional cities, with new ideas such as urban transportation vehicles and systems on 
the air. Rapid changes in technologies have supported modernisem to have more 
effects on the social economic sectors and generate new values and norms to reform 
social behaviors and reconstruct new landscapes and spaces. This thesis believes that, 
realizing a balance between technologies, places and life will be one of the most urban 
challenges in this century to give people a good sense of place and secure their health. 
Even, most western cities that were affected from modernism, however have 
intensified environemntal issues, and could not be able to give the people a good sense 
of place.  
In tomorrow's cities, advanced technologies and machines will be the dominant 
shapers of the spaces with the following general revolutionary effects:  
 Effecting on local and global mobilities and increasing compression of time, 
space, and place 
 Effecting on the pattern and rate of activities and emerging new dramatic 
changes in human and natural landscapes. 
Today, technologies are the critical part of daily life; therefore, managing and 
building a city just based on the architectural or planning theories and tools cannot be 
enough to move new urbanization and city development towards sustainability 
considering health and safety. Having a comprehensive view and proper 
understanding of the world's changes helps avoid any one-dimensional view in 
studying cities with multidimensional and complicated problems. This thesis belives 
that, studying technical forces must be an inseparable part of today and future urban 
studies and planning for sustainably shaping tomorrow's cities. Human behavior and 
lifestyle changed by changing and progressing technological tools, machines, and 
spaces, and helped us construct more complex and enormous constructions and spaces 
that we could not do before. Tools have been always a significant part of human life 
74 
 
and civilization and will remain so. Humans have formed, structured, and shaped their 
settlements based on the need, behavior, and tools Figure 49. 
A shift from a traditional lifestyle to a 
new and modern lifestyle in 
consequence of modernization and 
definition of new need with regarding 
social, cultural, and technological 
progress and evolution
 
Figure 49 A shift from the human‘s traditional lifestyle to the new and modern lifestyle. Designed by the author. And the 
first picture from the right at the top of this presentation was acquired from (Goswami, 2020), and the last picture from the 
left at bottom of this presentation was acquired from (de labour, 2020) 
 
For example, it is clear if we argue that the nature and structure of historical cities 
referred to the era that was constructed based on local time and conditions. 
Regardless, how much the nature of historical cities contradicts modern cities, both 
are responsible for giving the people a good sense of place. But the quantity and 
quality of human needs, activities, norms, values, and abilities have been affected by 
the progress of technological tools over time. And today's cities are experiencing 
different conditions of space and time owing to the new smart technological tools and 
big data. And on the one hand, we can't prevent or restrict development trends. On the 
other hand, this is a complex challenge to limit the adverse effects of technologies on 
daily life and environmental degradation. Because of technological urbanism, carrying 
on the safety and health of people and cities will be one of the main challenges of 
tomorrow's cities.  
Regarding technological urbanization, comprssion of the time, and complixity of 
the place and space, we do not know where we are going, and what will be happened 
75 
 
negatively as a consequence of technological urbanization! But this thesis belives that, 
emerge of Urban Sustainable Development Agendas (USDA) and mobilization of all 
cities and governments to commit to this Agenda's principles are a conscious 
movement to direct development towards a projected future. It helps to have a shared 
goal for organizing global actions to shape a common future concerning safty and 
sustainablity.  
 
 
Figure 50 looking at the cities from the lens of technological urbanization  (by the author) 
 
4.10.2. Economic cots 
Land value plays a significant role in allocating land and shaping the pattern, 
content, and structure of today's cities (Robert W. Burchell, Anthony Downs, Barbara 
McCann, Sahan Mukherji, 2005), (Chris Couch, Gerhard Petschel-Held, Lila 
Leontidou, 2008). It means any growth or reduction in the price of land parcels can 
increase or decrease the consumption of land parcels. In other words, the intensity of 
uncontrolled sprawl growth will be increased or reduced by land value. But it is 
different regarding urban zones. Generally, the density of space, place, elements, or 
activities tends to decrease from the center to the outside of cities Figure 51. 
76 
 
 
Figure 51 Different densities of land consumption between the urban, suburban, and rural areas (by the author) 
 
For example, in Dhaka, the increase of land values expanded housing projects in 
non-development zones of this metropolitan area near flood zones, lakes, ditches, 
freshwater canals, etc. (Alam, 2018). 
 
 
Figure 52 Living on the water, the new housing development project for the middle class, Dahaka, Pakistan, (Shafi, 
2011). 
 
Ottensman has done an empirical study that included fifty-one metropolitan areas 
on "Urban Sprawl, Land Values and the Density of Development." And the results 
have shown that a one percent growth in the population had increased the land value 
between twenty-five up to fifty dollars per acre at the whole of study areas 
77 
 
(Ottensmann J. R., 1977). Usually, landowners defer the development of their land 
parcels and sell parcels some years later to fill out additional land costs and attain 
more profit (Clawson, 1962). Because, population growth increases land demands 
and, it raises the land value. So landowners and stakeholders constantly monitor and 
analyze population and economic changes (Christopher Slemp, Mae A. Davenport, 
Erin Seekamp, Joan M. Brehm, Jon E. Schoonover, Karl W.J.Williard, 2012). Land 
value and population growth have a close linkage with the density of development. 
Large-scale migration and immigration to big cities have pressure on urban lands and 
spaces. 
Low land value is one of the main factors that have made agricultural lands 
vulnerable in front of urban expansion, which escalated by home builders to achieve 
more profits (Fischel, 1982) (Karakayacı, 2018). Because, as long as selling a land 
parcel gives landowners more profit than planting, so they try to be rich through an 
easier way. Maybe, increasing the price of agricultural goods will be one of the best 
strategies to encourage farmers to keep farming instead of selling, and of course, this 
strategy is effective to control sprawl growth. 
Uncontrolled land segregation and low-density development make the land market 
unstable and growth the land value (Paavo Monkkonen, Erick Guerrac, 2018)  (Zana 
Naab Francis, Dinye Romanus Dogkubong, 2013). Suburbanization and nonstop land 
segregation have increased the cost of the building because of distance and 
transportation costs. Distance has imposed additional costs for constructing and 
maintaining new infrastructures and also providing public service (Roman Trubka, 
Peter Newman, Darren Bilsborough, 2010). Indeed, suburbanization grown by using 
the potentials of natural resources inefficiently and imposed severe costs to societies 
and the environment. For example, a study on the "cost of water and sewer 
infrastructure" has shown that the establishment of infrastructures in the sprawled 
areas imposes expensive and extra costs to the cities compared to other zones located 
in the insight of a city (D’Amato, 2010), (Maria-Pia Gennaio, Anna M.Hersperger, 
Matthias Bürgi, 2009). Also, in further research, were used 12 variables such as 
garbage collection, the establishment of public safety against crime and disasters, 
78 
 
provision of services, education, library, etc.., to study the interactions between the 
density and general costs by per capita. And finally, the results have indicated that the 
intensification of density decreases the per capita of cost of services (John I 
Carruthers, Gudmundur F Ulfarsson, 2003). The continuation of suburbanization 
affects the type and area of services, investment rate, and quantity and quality of 
development projects in sprawled cities. In these cities, suburbanization declined the 
operating radius of central cores and changed the circulation of distribution of services 
at the whole of cities.  
The other point is that, the rate of tax in the suburbs is lower than in the centers of 
cities, and this factor decreases the ability of centers to sell of competitive products 
(Myron Orfield, 2011). Also it affects urban mobility, makes suburbs more attractive 
and motivates residents to move from the main body of cities towards the suburbs or 
exurbs (David R. Morgan, Patrice Mareschal, 1999). For example, in the American 
cities many people that today live in the suburbs first have lived in the city centers. 
Because after the migration of people from other regions to the city centers, most of 
old habitants moved from centers to suburbs or urban fringes between 1950 and 1960. 
And this issue degraded the gravity and attraction of city centers (Levin, 1974).  
4.11. Smart growth and counterurbanization 
Considering the increasing public concerns on the negative consequence of sprawl 
growth patterns, supporting desprawlization ideas and long-term strategies in today’s 
urban development policies is essential. And in this regard, some planners and policy-
makers have been taken into account some approaches and strategies to control, and 
manage the sprawlization as follows:  
 Reviewing and developing regulations and legislation to protect the 
environment (Harriet Tregoning, Julian Agyeman, Christine Shenot, 2002),  
 Developing sustainable and effective public transformation systems (Turner, 
2007),  
 Redefine of urban functions for the non-functional and dead spaces (Ewing, 
1999),  
79 
 
 Sustainable land use planning to control and decline degradation of 
segregated valuable land resources (H.J. Heineke, W. Eckelmann, A.J. 
Thomasson, R.J.A. Jones, L. Montanarella, B. Buckley (eds.), 1998).   
In the late twentieth century, new theories such as Smart Growth was proposed to 
control and direct urban physical growth, especially in sprawled zones. In the early 
1970s, urban planners considering the costs and difficulties of acquiring land to 
construct and expand highways tried to develop compact cities and communities 
approaches and adopt many regulatory approaches related to smart growth. Today, 
researchers employ this theory during planning and policymaking steps to integrate 
and protect the environment, sustain economy and resources, improve social justice, 
and enhance the quality of life. For example, in some research, smart growth was 
introduced as a promoter of high-density urban development and used to control the 
sprawl growth pattern or to revitalize unproductive urban spaces (Downs, 2005). In 
this regard, this thesis believes that, the Big Building with Multiple Functions Model 
(BMF) can be one of the best strategies to increase the capacity of land parcels, and 
change the direction of physical development in vertical form instate of horizontally 
like sprawl form. BMF model decreases the dependency of cities on land and also 
environmental degradations Figure 53.  
 
Figure 53 A sample model of compacted and multifunctional building regarding the principles of smart growth (mixed-
use) (barbara-porada, 2013) 
80 
 
4.12. Concept of urban smart growth 
Based on the philosophy and principles of smart growth, the American Planning 
Association noted that the smart growth theory helps reconstruct the allocation of 
resources from regionals to the local communities (O'Connell, 2009). The goals of the 
smart growth theory are not in contradiction to urban growth, and these goals attempt 
to propose a form of urban growth to a) sustain urban development, b) reconstruct and 
optimize unproductive spaces c) promote urban efficiency and liveability (Nabiollah 
Kolbadi, Mahmoud Mohammadi, Fahimeh Namvar, 2015). But It doesn't mean that 
the smart growth theory claim that the other past urban theories and plans were not 
smart. In fact, the smart growth theory attempts to meet reasonable and practicable 
strategies through a smart (cooperative and interactive) decision-making process 
considering todays’ cities' conditions, potentials and challenges. Urban researchers in 
urban studies have always integrated this theory with the other urban ideas and 
concepts such as  Sustainable Development, Green Growth, and Compact City to find 
practical solutions towards realizing sustainable urbanization. 
Guidelines •Adaptation of new legislation and regulation for providing facilities for smart urban growth
•Update and generate new fields in the urban planning 
for urban discipline on the trajectory of smart growth•Establish urban smart growth partnership groups
•Building smart and digital infrastructures & Services
authorities
•Define and evaluate the role and performance of 
Guidelines economic sectors regarding principles of smart urban 
growth
•Create specific groups and teams to identify investment 
for Private fields and resources
•Developing services in conformity with smart growth
Sectors 
 
Figure 54 Guidelines for urban authorities and private Sectors (by the author) 
This theory promotes "participation" at all the decision-making processes (L. 
Christopher Plein, Jeremy Morris, 2017). In fact, smart growth theory invites all social 
groups with different opinions or views to participate in the urban development 
81 
 
process and making development policies based on a collective wisdom. This theory 
maximizes participation by assuring the citizens that their views are central and will 
be considered in the decision-making process. Because the mutual respect and 
interaction between dwellers and planning teams play a substantial role in 
implementing successful urban development plans. 
 
Figure 55 Conceptual model of a smart city according to the principles of the Smart Growth theory (Schilling, 2015)  
 
The significant effects of the smart growth theory: 
1- Increasing the efficiency of mixed-use buildings 
2- Enhancing advantages of a compact building 
4- Increasing productivity and efficiency of urban spaces and social dynamism  
5- Protecting open spaces and valuable resources  
6- Attempting to develop and employ some strategies with more predictability  
7- Providing a sustainable form of transportation systems and options 
8- Encouraging people and stakeholders to participate in the decision-making 
process to meet the best development strategies (Lin Ye, Sumedha Mandpe, Peter B. 
Meyer, 2005 ), (Zhang, 2017). 
82 
 
 
 
 
 
 
 
 
Chapter Five 
 
 
 
 
 
 
 
 
 
 
 
 
 
83 
 
 
 
 
Land use planning 
 
 
 
5.1. Land 
There are different descriptions for the word "land" in the scientific fields. 
Examplarly, for economists, the definition of land mainly concentrates on the 
economic characteristics of the land. Or geomorphologists conceptualize and classify 
a land regarding topographic and bathymetric features. For geomorphologists, the 
type, material, and form of the land are more significant than the economic 
characteristics of a land parcel.  
Cloak (1989) defined land as a basic form of private ownership that can be traded 
or used as public ownership (Isilda da Conceçäio, Joäo Nhantumbo, 1997).  
This study defined land as a base for activities considering the social-economic and 
environmental aspects for each land parcel. 
Land activities are the leading factors that have accelerated land cover changes. For 
example, on the one hand, we are experiencing massive changes in technologies and 
tools since the 1970s. But, on the other hand, these changes increase the presence of 
technologies and machines in humans' daily life and changes human behavior. As a 
result, changing human behavior changes human activities, and changes in human 
activities will change places and spaces. Technological developments have imposed 
extraordinary changes to the spatial forms and interactions, communication, and 
transportation systems. And these significant changes have increased the sphere of 
84 
 
influence of cities and developed physical, social, cultural, and economic sectors.  As 
a result, have provided millions of new job opportunities, especially in urban areas, 
and increased welfare, public health, and population size. Hence, rapid urbanization 
and agglomerated cities have increased demands for new land parcels regarding the 
type of activities and densities. 
5.2. Land use 
In general, land use plans emerged in the 1950s and was included remarkable 
principles and guidelines for each land parcel and type of activity considering social-
economic aspects to direct urban growth and development (Edward J. Kaiser, David 
R. Godschalk). Land use planning is an activity that involves human interaction with 
the land (Grzybowski, 2014). In other words, the land-use plans rearrange land and 
activities for specific goals (Kumar P. , 2013). 
Later many researchers have been tried to develop this model as Chapin, who has 
played a significant role in developing principles of the urban land-use plan between 
the 1950-the 1960s (F.Stuart Chapin, 1965). In general, this plan embraces the 
following steps: mapping, predicting, and planning urban lands. And also, a land-use 
plan covers the following actions, including locating, determining the type of activity 
for each land parcel, such as commercial, retail, residential, cultural, educational, etc. 
Today, principles of this plan regarding the spatial complexity will be reviewed and 
tried to import environmental concerns and sustainable development principles in the 
land use planning studies to control and diminish environmental tensions like climate 
changes, air pollutions, or degradation of natural capitals. 
Regarding this thesis, land use planning is a practice to provide a safe and 
pleasurable place and accommodate human behaviors with the daily needs considering 
the local potentials and limitations. In this state, human needs are regarded as leading 
landscape shapers, but the rate of changes depends on the role and levels of activity.  
85 
 
 
Figure 56 A conceptual representation of land use planning (by the author) 
Land use maps can be regarded as a well-connected thematic plan and prepared 
through the technical and official processes. Today, these plans are employing by 
planners for monitoring recent changes in the land development process, better 
direction and management of land development, also identifying new sites for 
development (Matsuoka, 2004). Land-use planning practice is regarded as a 
mechanism that helps us meet the needs and interests of private or public sectors. 
 
 
Figure 57 The main pillars engaged in the evolution of land use planning (by the author) 
Regarding this thesis, the following three factors play significant roles in the 
change of the land use types and activities including Time, Place, and Space. 
86 
 
5.2.1. Time 
The factor Time is a significant part of occurred changes in landuse types and 
activities and quantitatively or qualitatively. For example, since 19th century have 
been occurred significant changes in the urban activities and land uses. And these 
changes have changed or even reformed urban forms, spaces, and interactions among 
humans, activities, and places. Therefore, redefinition of "land" and "land use" is 
required in the land-use studies regarding these massive changes. Moreover, it is 
necessary to understand better the new phenomena and their interactions over time. 
 
Figure 58 Change and progress of land use quantitatively and qualitatively (by the author) 
 
5.2.2. Place and space 
In this study, "place and space" are regarded as two inseparable parts with 
significant roles in creating and changing phenomena such as land use.  
"Place" is defined as a physical or nonphysical base for human activities and 
divided into known space and unknown space. The interactions between the physical 
or nonphysical places have reshaped the type of land use and activities in a large-scale 
and multiple set of spaces and places. For example, cyberspaces have changed land 
uses by changing and reforming human activities and behavior. Please consider the 
consequences of these changes on the physical and nonphysical urban elements. The 
cyberspace reshapes the environment, generates new physical forms in urban spaces, 
and reconstructs places and buildings. In the following decades, growing the 
87 
 
dependency of humans on the internet, will increase the presence of cyberspace in 
reshaping and rearranging physical spaces and forms remarkably.  
 
 
Figure 59 Develop and increase of land use activities considering time, place, and space (by the author) 
 
 
Figure 60 The interaction and communication between human's real-world and cyberspace (by the author) 
 
88 
 
5.3. Sustainable land use 
Since the last decades many researchers have studied "land use planning and 
sustainability" from different aspects, especially after publishing the two following 
reports including: the report of "Brundtland Commission" in 1987 on the, "Our 
Common Future," and the report of "Earth Summit" in Rio de Janeiro in 1992 (UN-
HABITAT, 2010). These conferences have progressed using the principles of 
sustainable development in urban land use planning globally (Xiaoling Zhang, Yuzhe 
Wu, Liyin Shen, 2011). Management and protection of land and environment are tied 
to the sustainability of social, and economic sectors. In this regard some theories such 
as Mixed-use and Compact Development were developed to improve land use 
management regarding sustainability. And also to enhance the efficiency of land 
parcels and decreased the consumption of raw lands. 
After the appearance of sustainable development theory, researchers have 
developed or promoted this theory in different fields including technologies, politics, 
and industries, to apply the principles of sustainable development in the social and 
economic strategies. For example, In 1993, the American food and agriculture 
organization has provided a framework for assessing land use and management 
sustainability. According to the designed framework, sustainable development 
principles have also been employed for measuring land development and helped to 
realize an effective and sustainable form of land use.  
5.4. Land management and land administration 
United Nations Economic Commission for Europe UNECE (1996) had explained 
the land administration plan to provide a big databank around land use data and land 
tenure. In contrast, land management is considered a set of policies, legislation, and 
functions for land development. The land administration is an attempt to preserve the 
potential of land, run sustainable land uses, and conserve valuable natural resources 
(Peter Dale, John McLaughlin, 2000). Given Enemark (2003), land management 
includes all sectors mentioned above in realizing sustainable land development 
(Agnieszka Dawidowicz, Winrich Voß, Bernd Leonard, 2013).  
89 
 
 
Regarding UNECE, the land administration system is designed for achieving the 
following goals: 
 Increasing the security of land ownership and reducing conflicts 
 Monitoring the land development 
 Land management considering the environmental limitations 
 Providing a data bank of land ownership 
The land administration helps allocate land resources concerning social-economic 
factors and provides needed lands for housing projects. Or providing a databank of 
land ownership helps for providing urban infrastructures. The informal land tenure 
and illegal land grabbing due to the lack of comprehensive lands ownership databank 
have expanded the urban informal sectors. Tracing and recording land use changes 
help to manage and monitor urban lands effectively (Agnieszka Dawidowicz, Winrich 
Voß, Bernd Leonard, 2013). Unfortunately in many countries, because of the lack of 
efficient land management system, controlling the land value and land use changes are 
one of the main challenges particularly in developing countries (Daniel Hoornweg, 
Mila Freire, 2013). For example, suburbanization has progressed informal settlements 
and in some cases, people occupied land parcels illegally and built up without a 
building permit (Kwasi Gyau Baffour Awuah, Felix Nikoi Hammonda, Jessica 
Elizabeth Lamond, Colin Booth, 2014). Hence, using an efficient land administration 
system can help to manage land-use changes (UN-HABITAT, 2010).  
 
General parts of land administration system 
Landownership
Land use types
Land use development
 
Figure 61 General parts of land administration system (by the author) 
90 
 
In general, the land administration system (LAS) records the following information 
for a land parcel: 
- Landownership 
- Land use types 
- Land use development 
5.4.1. Land ownership 
It refers to the identification and recognization of people's real estate in a place 
through law (Kimani, 1972) . Regarding the factor of time, ownership can be 
temporary or permanent. Regardless types of land ownership, securing the right of 
ownership is very important for owners. Ownership has various types such as: rental 
houses (private and public), Housing co-op, House lease, Owner-occupancy, 
Emergency housing, and informal settlements.  
5.4.2. Land-use types 
The factor land use type is employed to detect and define types of land use for each 
parcel in a databank, such as, residential, agricultural, industrial, commercial, etc.,. 
5.4.3. Land use development 
It includes all roles, actions, and strategies for the development of land parcels 
(Agbosu, 1980). 
Numerous of land parcels and owners at the regional and national levels shows the 
necessity of an efficient land administration system. For example, industrialized 
countries have provided required infrastructures and tools for an effective land 
administration system especially using Geographical Information System (GIS), 
Remote Sensing, and satellite images, to trace and control land-use changes. Such 
advanced technologies reduce the factor time during data collection. But one of the 
other main tools is, public participation For data collecting and providing an effective 
land administration databank. Therefore, developing some strategies considering local 
conditions and potentials for encouraging people to participate in this project is 
necessary. 
91 
 
5.5. Urban land-use planning 
In urban studies, the concept of urban land use planning has been employed and 
defined vary regarding the geographical and local conditions (Wei-Ning Xiang, Keith 
C Clarke, 2003). Since the last decades, most of land use planning studies were "issue-
oriented" to identify the reasons of inefficient land development strategies and policies 
(Caroline Raphael, 2011), (Raphael, 2011). Urban land-use planning can be 
considered as a conscious practice for the management of urban lands regarding the 
social-economic conditions, environmental concerns, and limitations. This plan is a 
try to meet the needs of people and balancing the pattern of activities. The 
implementation of this plan encompasses a set of tools, data, methods for analyzing, 
assessing, measuring and evaluating the urban development, urban growth, urban land 
market, land demand and supply. And also this plan studies the social, political, and 
economic factors in land use planning.  
This study believes that, urban land-use planning determines people's interactions 
in a place. Also it is regarded as a spatial distribution of the urban functions and 
allocation of spaces to the activities such as residential, commercial, industrial, and 
ect. (Yu-Hsin Tsai, 2015), (White, 1979). For defining a type of activity for a land 
parcel paying attention to some factors is important such as: slope, soil, climate, 
density, distribution, compatibility, desirability, dependency, capacity, accessibility, 
and functions (Shaheen L. , 2006), (B. L. Turner, William B. Meyer, David L. Skole, 
1994).  
 
Figure 62 The important factors in the determination of activities for land parcels  (by the author) 
92 
 
5.6. Complexity in the process of urban land use planning  
Since the last decades the land-use planning practice became more complex than 
before. Because the unpredicted internal and external dynamic factors have always 
faced this plan with some unwelcome challenge So, we need new land-use planning 
models to analyze many criterias simultaneously and comprehensively. In an complex 
urban system, there are many influencive factors among people, activities, and land 
parcels that faces the implementation of land use plans with difficulties. According to 
this study, in Iran, human factors more than the other factors have faced this plan with 
many challenges.  
The general parts of this complexity includes players, spatial setting, and 
cooperating process.   
Players: 
According to this study, the involvement of people and groups in the land use 
planning process regarded as one of the main drivers and shapers of an "urban spatial 
organization" that encompasse both human and natural spaces. The duration of the 
execution depends on the urban authorities and participation of groups and 
organizations in the planning process. But depending the case and interests, the power 
groups under political backing endeavor to increase their financial and political 
interests. If their request encountered a disagreement in the planning process, they 
tried to manipulate the plan and impose their interests in the project by force or other 
tools. So, respect to the law and order, increasing presence and power of the 
regulatory agencies help to diminution such problems considerably and implement the 
plan successfully. 
Spatial setting: 
Divers of spatial functions regarding different land-use types have escalated the 
complexity of spatial settings. Therefore understanding the compatibility or 
incompatibility of spatial roles with these activities is challenging. How much can it 
be challenging if we use a land parcel for an spacific activity that actually is not 
allowed in a land-use plan? For example, using a land parcel with educational aims for 
93 
 
commercial activity? Regarding the area of a parcel and the necessity of the activity it 
can influence all social-economic interactions in a city zone or even at the whole of a 
city. It can intensify traffic by increasing the rate of daily trips and mobility in an 
especific zone of a city. But in this example we talked about a zone of a city. Imagine 
if all cities of a country like Iran have been faced with this issue! In Iran, 
unfortunately no city could successfully implement a land-use plan! Generally just 
between ten to twenty percent of the plan’s goals became realized. About eighty 
percent of the proposed activities and allowed densities for each parcel in this plan 
couldn't come true. Now you can imagine what disaster happened to the Iranian cities. 
This is one of the main challenges of Iran's contemporary cities. This difficulty 
created many issues and imposed pressure on the capacity of infrastructures. 
Cooperating processes: 
Cooperating practice and how it can be succeeded hang on some political and 
administrative structures and social-economic capacities in the land use planning and 
executing phases (Arnab Chakraborty, Nikhil Kaza, Gerrit-Jan Knaap, Brian Deal, 
2011), (A.Huberman, 1990). The cooperation improves communication among all 
project parts and increases the proportion of a successful implementation of the plan.  
 
• Sector • Sector 
A B  
AB BC
DA CD
• Sector • Sector 
D C
 
 
Figure 63 Conceptual networking model to have exact data sharing between sectors in a system (by the author) 
 
94 
 
If we consider the land-use plan as a project that tries to realize harmony among the 
people, activities, and needs to minimize the tensions between humans and the 
environment. So, in this sense, the environment is conceived as an independent factor 
in land use planning. The environment is the space where people are working and 
living and, because of that, constantly is in changing.  But the dimensions of change 
are conditional, and depending on the place, forces and humans' activity will be 
different. But it should be noted that the connections and interactions between urban 
activities determine land use segregation or integration. 
5.7. The land use classification 
Land use classification is a more general map to identify and specify the type of 
land uses on a map on a large or small scale. And the covered features on this map 
will be different thematically; exemplary contains forest, mountain, built-up areas, 
rivers, cultivated lands, and vegetation covers. This plan helps the planners and 
organizations to classify all environmental elements, potentials, capacities, and 
limitations in a particular place. For example, encourage urban growth in some places 
with the lowest ecological concerns and limiting urban expansion in the natural 
protected areas (Daniel Hoornweg, Mila Freire, 2013), (Arend Ligtenberg, Arnold K. 
Bergt, Ron van Lammeren, 2001). 
In urban studies, land use classification regarded as a regulator tool that helps the 
local and national organizations to monitor and control land cover changes and 
determine what parcel, when and under what rule and legislation must be used. In 
addition, it is a supportive tool to protect non-development areas, especially 
vulnerable regions. Additionally, this model provided a prototype concept for land 
classification and prioritization of planning area in three classes: 1- protected natural 
areas, 2- Cultivating lands, 3- Settlements.  
Protected natural areas: this class has the highest priority and includes all places 
that must be protected against any buildings and constructions. 
Cultivating lands: this class has the second priority and includes cultivating lands 
such as agricultural lands, forests, etc. (Edward J. Kaiser, David R. Godschalk, 1995). 
95 
 
Settlements: this class has third priority and includes all built up areas for living, 
working, and other activities. 
96 
 
 
 
 
 
Chapter Six 
 
 
Methodology 
 
 
 
 
 
 
 
 
 
 
 
 
97 
 
 
Methodology 
 
 
The type of this thesis considering the aims is descriptive and analytical to describe 
the current issues and give reliable answers to the questions. Methodologically, this 
thesis is qualitative and quantitative and uses used statistical data, mathematical 
models, and softwares to analyze and measure social-economic changes, urban 
development, and sprawl growth of Sari city. 
6.1. The applied demographic projection models 
6.1.1. Projection of population growth 
Population predictions are like 'what-if' scenarios to determine how the population 
will grow in the expectation (United States Census Bureau, 2017). These projections 
are essential to calculate the population's force on this planetoid and the communities' 
future well-being (Kaneda, Toshiko, 2014). Patterns of population growth take trends 
in social development and employ predictions into the prospect (Roser, 2019). These 
models use trend-based presumptions concerning how populations react to business, 
social and technological powers to determine how they influence fertility, mortality, 
net migration, and population growth (Office for national statistics, 2021). 
In this chapter, some prediction models for population change are provided 
included the Modified Exponential Model and the Linear Regression Model to predict 
the population growth in the next few years and decades. 
6.1.2. Modified exponential model 
Exponential growth is a example of data that reveals greater increases with passing 
time, creating the curve of an exponential function (Chen, 2021). According to 
Malthus' model, once population size exceeds available resources, population growth 
decreases dramatically. This accelerating growing population size is 
98 
 
called "exponential growth," signifying that the population increases by a fixed rate 
each year (Zehnder, 2021). 
This type of growth can be represented by applying a mathematical function known 
as the exponential growth model: 
𝑃(𝑡+𝑛) = 𝑃(𝑡)(1 + 𝑟)
𝑛 
𝑃(𝑡+𝑛): population in the year t+n (end of period) 
𝑃(𝑡): population in the year t (start of the period) 
𝑛: period considering (month, year, half of a year) 
r: the annual growth of population  
So that r (the annual growth of population) will be calculated by using the 
following formula: 
𝑛 𝑃(𝑡)
𝑟 = ( √ − 1) × 100 
𝑃.
In this model, the amount of population growth is addressed to the size of the 
current population. The proportion between the population growth and the total 
population is fixed (Mirnajaf Mossavi, Hassan Hekmatnia, 2011). 
6.1.3. Linear regression model 
Linear regression enables you to make predictions on the data, and it is intuitive 
and easy to understand (Ognjanovski, 2018 ). 
Using the relationship between two variables, this model can calculate and estimate 
a variable by another variable. So that the variable Y changes concerning the time X. 
Therefore, can realize a linear relation between two groups of variables as follow: 
Y= ax+b 
Linear equation 
The amount of a and b is coefficients that can be calculated through the following 
formulas: 
99 
 
∑ 𝑥𝑦
𝑎 =  
∑ 𝑥2
∑ 𝑦
𝑏 =  
𝑁
N: is the number of periods (Mirnajaf Mossavi, Hassan Hekmatnia, 2011). 
6.1.4. Elasticity analysis  
This study has applied elasticity analysis to know which life-history stages most 
impact on population growth. Sensitivity and elasticity are long-established, widely-
used instruments for pinpointing effective peculiar demographic rates in this process 
(Lee, 2016). Elasticity analysis is a manageable initial measure in clarifying essential 
issues in evolutionary and population science.  (Benton, Tim & Grant, Alastair, 2000). 
Elasticity analysis estimates the proportional change in population growth rate for a 
given change in a population rate parameter (Bart W. Durham and Gene R. Wilde, 
2004). 
This model is an index to estimate the percent of the urban population versus the 
total population. It means how much has increased or decreased the city's population 
as a case study for each one percent increase in the total population at the (national, 
regional, or local) levels in a specific period. 
This study used the following formula for estimating the elasticity rate of 
population growth: 
𝑌𝑢(𝑡, 𝑡 + 10)
𝐸(𝑡,𝑡+10) =  𝑟(𝑡, 𝑡 + 10)
E: is equal to the elasticity rate for a period  t,t+10 
Yu: the annual growth rate of urban population  
r: the annual growth rate of the total population 
6.2. The Rank-Size Rule and Zipf’s law 
Flix-Auerbach is a German geographer and, in 1913, has provided the Rank-Size 
Rule to analyze the relationship between the size and place of cities (Mirnajaf 
100 
 
Mossavi, Hassan Hekmatnia, 2011). And later in the 1940s, George Zipf identified a 
curious regularity in the distribution of cities of varying sizes; if cities were ranked 
from largest to smallest populations, then 
𝑃1
𝑃𝑟 =  𝑅𝑏
P1: the population of the largest city or town,  
PR: is the population of the smallest city by rank, 
b: is a coefficient that must be established through empirical observation for each 
investigation. The superior the value of b, the steeper the slope, and the greater the 
primacy of the largest city or town. 
George Zipf defines the above formula in a logarithm form as follow: 
𝐿𝑜𝑔𝑃𝑟 = 𝐿𝑜𝑔𝑃1 − 𝑏𝐿𝑜𝑔𝑅 
𝑃
𝐿𝑜𝑔 1
𝑃
𝑏 = 𝑟  
𝐿𝑜𝑔𝑅
The contribution of rank-size rule in urban regional planning: 
 It helps in the understanding of the relationship between rank and population 
size of settlements. 
 It helps in analyzing the settlement networks. 
 It explains settlements concerning economic activities as an increase in 
activities increases the population. 
 It explains the imbalance between the settlements due to rapid growth in 
population or activities (Kumar V. , 2017). 
6.3. Regression model 
It is normally possible to relate the ranks and sizes rule by using regression analysis 
(Minimum squares method) and calculate the rate of the line of slope (b). 
Y= a+bx 
101 
 
b: the rate of the line of slope 
a: is a fixed value 
x= is the logarithm of the rank of a city 
y= is the logarithm of the size of the population of a city 
If b>1 means there is no balance between the size of population and rank of cities, 
and most of the population is moved to the big cities. And if b<1, means a balance 
between the size of population and rank of cities and importance of the medium and 
small-sized cities in the urban hierarchy.  
6.4. Location Quotient model (L.Q) 
Location Quotient (LQ) is a useful way of quantifying how concentrated industrial, 
agricultural, and services in a region as compared to the nation (Strotebeck, 2010). It 
can show what makes a individual region unique compared to the national average 
(Walter, 2019). Utilizing the location quotient is a powerful way to identify growth 
opportunities and comparative regional advantages (Goodwin, 2018). 
𝑇𝑁𝑖
𝐿. 𝑄 =  𝑇𝑁𝑎   
𝐶𝑁𝑖
𝐶𝑁𝑎
𝐿. 𝑄= Location Quotient 
𝑇𝑁𝑖= the number of employments in i sector locally 
𝑇𝑁𝑎= Overall employment locally 
𝐶𝑁𝑖= the number of employments in i sector regionally or nationally 
𝐶𝑁𝑎= Overall employment regionally or nationally 
 If 𝐿. 𝑄 > 1 means the place that can be a city is the exporter of that product or 
service, and if 𝐿. 𝑄 < 1 means the city is an importer of that product or service. And if 
𝐿. 𝑄 = 1 means the city is independent. 
102 
 
6.5. Entropy Index 
This model helps measure the inequal distribution of population and cities in the 
urban network at the regional and national levels. It helps to know if a balance is 
established between the population and size of cities in a metropolitan area. 
The formula for entropy is: 
𝐻 =  ∑ 𝑃𝑖𝐿𝑛𝑃𝑖 
𝐻
𝐺 =   
𝐿𝑛𝐾
H= Sum of the frequency in the natural logarithm  
Pi= Frequency 
LnPi= frequency of the natural logarithm  
K= the number of classes 
G= the value of entropy  
According to the principles of the Entropy Index, (G) is the rate of entropy. If the 
rate tends toward the value (0), it means intensifying population agglomeration and 
imbalance in the population distribution. Suppose the value tends towards (1) or even 
more, so it means normal distribution of population and establishing a balance among 
the cities in an urban area. 
As presented in table 56, the cities are classified into different groups based on the 
population size in the first column. In the second column showed the real population, 
and then calculated rate of Pi: frequency, Ln (Pi) Ln Pi: Nehprii frequency logarithm, 
and Pi*Ln (Pi)]. 
6.6. Isard's Longitudinal and Transverse model  
This model is a method to analyze economic conditions to understand and project 
the share of economic sectors at the local, regional, and national levels. 
103 
 
In this matrix, x shows the percent of employment change at the national level, y 
shows the percent of employment change at the regional or city levels. 
 
Figure 64 Isard’s longitudinal and transverse matrix (by the author) 
 
Suppose one of the economic sectors is placed in part I. In that case, the sector has 
a better condition than the average economic growth at the local, regional or national 
levels. 
Suppose one of the economic sectors is placed in part II. In that case, it means the 
sector is less than the average economic growth of the nation and more than the 
average economic growth at the local or regional levels. 
Suppose one of the economic sectors is placed in part III. In that case, it means the 
average economic growth of that sector is less than the average economic growth at 
the local, regional, or national levels. 
Suppose one of the economic sectors is placed in part IV. In that case, it means this 
sector is more than the average economic growth of the nation and less than the 
average economic growth at the local or regional levels. 
𝑇ℎ𝑒 𝑏𝑒𝑔𝑖𝑛𝑛𝑖𝑛𝑔 𝑜𝑓 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑
𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑜𝑓 𝑐ℎ𝑎𝑛𝑔𝑒𝑠 = × 100 
𝑇ℎ𝑒 𝑒𝑛𝑑 𝑜𝑓 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑
104 
 
6.7. Lorenz Curve  
One of the methods to measure hierarchies of cities and spatial distribution of 
population in a metropolitan area. This curve has two axes, horizontal (x) and vertical 
(y) and values between 0-100 and means the percentage of cumulative frequency. 
 
Figure 65 A simple view of the Lorenz Curve (by the author) 
 
In order to show how the cities are populated in this curve, the axis X is used to 
indicate the cumulative frequency percentage of cities, and axis Y to show the 
cumulative frequency percentage of cities groups. 
The straight or normal line is the "line of perfect equality.  Continue of this text in 
the Gini coefficient part. 
6.8. The Gini coefficient 
The Gini coefficient is the area ratio between the line of ideal equality and the 
observed Lorenz curve to the area between the line of ideal equality and the line of 
perfect inequality. The higher the coefficient, the more unequal the distribution is.  
 
𝐴
𝐽 =  
𝐴 + 𝐵
 
J: The Gini coefficient 
A: The area between the Lorenz Curve and the normal line 
105 
 
A+B: are the areas of the parts A and B 
Based on the Gini coefficient, if G=0 means complete equality, G>0 and up to 
0.25, means relative unequal. If the result is between 0 .25 – 0.5 expresses Unequal; if 
between 0.5 – 0.75 means more unequal, and if between 0.75 – 100 says total 
inequality (Critical situation).  
6.9. MAXLIKE (Maximum Likelihood) 
The MAXLIKE module has provided the Maximum Likelihood procedure in the 
IDRISI Image Processing toolset to compensate for the main deficiencies of both the 
Parallelepiped and Minimum-Distance-to-Means procedures. The Maximum 
Likelihood procedure is based on Bayesian probability theory. The MAXLIKE 
module uses the mean and variance/covariance data of the signatures to estimate the 
posterior probability to determine which pixel belongs to predefined classes 
(Clarklabs, 2020). 
In many ways, the MAXLIKE module is similar to the MINDIST with the 
standardized distance option. The only difference refers to the MAXLIKE accounts 
for intercorrelation between bands (Reveshty, 2011). MAXLIKE incorporates 
information about the covariance between bands as well as their inherent variance and 
produces an elliptical zone of characterized signature but conceptualized (Paul, S. S., 
Li, J., Wheate, R., & Li, Y., 2018). In fact, it determines the posterior chance of 
belonging to each class, where the probability is highest at the mean position of 
classifications and falls off in an elliptical pattern away from the mean (Parth Sarathi 
Roy, Lars T. Waser, 2017). 
 
6.10. Land change modeler  
6.10.1. The Change Prediction Process in LCM 
Land change prediction is an empirical observation driven process in Land Change 
Modeler that moves in the following stages 1) Change Analysis, 2) Transition 
Potential Modeling, to 3) Change Prediction. It is based on the historical change of 
106 
 
land cover maps from time point 1 to time point 2 to project future scenarios (Kshitij 
Mohan, Praveen Kumar Rai, Varun Narayan Mishra, 2014). 
The Land Change modeler interface is structured around a set of six main tasks: 
 Change Analysis: Analyzing earlier landcover change 
 Transition potentials: Modeling the potential for land transitions 
 Change prediction: Calculating the possibility of change into the future 
 Planning: Calculating planning interventions 
 REDD Project: Estimating GHG emissions from REDD projects 
 Harmonize: Constructing land cover maps to use in Land Change Modeler (lab 
only launches when landcover maps are incorrectly formatted) (Clarklabs, 
2020) 
The landcover maps used by LCM must be formatted to meet the following 
conditions: 
1. legends in both maps are the same. 
2. Classifications in both maps are the same and progressive. 
3. Backgrounds in both maps are the same and have a quantity of zero. 
4. Spatial dimensions, including resolution and coordinates, are the same (R. K. 
Jain, Kamal Jain, S. Rehan Ali, 2017). 
6.10.2. Change analysis 
The change is calculated concerning time point 1 and time point 2 between two 
land cover maps in Change Analysis. Identified changes are transitions from one land 
cover state to another. It is likely that with many landcover classes, the possible 
combination of transitions can be very large. What is important is to identify the 
dominant transitions that can be grouped, modeled, and termed submodels (Nidhi 
Nagabhatla, C. Max Finlayson, Sonali Seneratna Sellamuttu, 2012).  
107 
 
6.10.3. Transition Potential Modeling 
Transition Potential Modeling is the subsequent phase in the change projection 
process, where we can identify the potentials of land to transition. This step will create 
potential transition maps of suitability for each transition. In LCM, a collection of 
potential transition maps is organized within an empirically evaluated transition sub-
model that has the same underlying driver variables (Clarklabs, 2020). A transition 
sub-model can contain a single land cover transition or a group of transitions that have 
the same underlying driver of variables. These driver variables use to model the 
historical change process. For instance, if you are modeling deforestation due to 
agriculture, river variables to consider would be slopes, proximity to roads, or 
previously deforested areas (Florencia Sangermano, J Ronald Eastman, Honglei Zhu, 
2021). Transitions are modeled using either a multilayer perceptron (MLP) neural 
network, logistic regression, or a similarity-weighted instance-based machine learning 
tool (Same Weight) (Rahim Aguejdad, Thomas Houet, Laurence Hubert-Moy , 2017). 
Once calibrated, the model is employed to predict future scenarios. 
6.10.4. Change prediction 
The third and final step in the Change Analysis is Change Prediction. Using the 
historical rates of change and the transition potential model, LCM can expect a future 
scenario for a specified future date. In its easiest form, the model will define how the 
variables influence future change, how much change took place between time 1 and 
time 2, and then calculate a relative amount of transition to the future date (Clarklabs, 
2020). To remake the model more robust, the Land Change Modeler make available 
for the incorporation of constraints and incentives, such as zoning maps; and planned 
infrastructure changes, such as new roads or land cover development. Driver variables 
can also be dynamic in nature so that at regular interim intervals, they can be 
recalculated and reenter the model (Megersa Kebede Leta, Tamene Adugna Demissie, 
Jens Tränckner, 2021). For instance, you may have as one of your driver variables 
distance from formerly deforested areas. This variable could be recalculated at regular 
intervals as and cover transitions from forest to agriculture. 
108 
 
6.10.5. Hard classifying 
The distinguishing characteristic of complex classifies is that they all decide the 
landcover class to which any pixel belongs. TerrSet offers a host of supervised 
classifiers in this group. Some like (MAXLIKE) means maximum likelihood, and this 
procedure is unquestionably the most widely used classifier in the classification of 
remotely sensed imagery.  
6.10.6. Soft classifying 
Contrary to the hard classifier, the sot classifier does not decide the landcover class 
to which each pixel belongs. Instead, they develop statements of degrees to which 
each pixel belongs to each of the landcover classes being considered. Thus, for 
example, a soft classifier might indicate that pixel has a 20.72 probability of being 
forest, a .24 probability of being pasture, and a 0.04 probability of being bare ground. 
A hard classifier would resolve this uncertainty by concluding that the pixel was a 
forest. However, a soft classifier makes this uncertainty explicitly available for 
various reasons (Clarklabs, 2020).  
6.11. Markov model 
Markov model has been broadly used in ecological modeling (Nouri, J., 
Gharagozlou, A., Arjmandi, R. et al. , 2014). Markov model considers past states to 
predict how changes a particular variable over change modeling is promising because 
of its ability to quantify the states of conversion between land-use types and the rate of 
conversion among the land-use types (Ye B., Bai Z., 2008). A homogenous Markov 
model for predicting land-use change is presented mathematically as follow; 
 
and 
 
109 
 
where, L(t+1) and L(t) are the land-use status at time t+1 and t respectively. (0≤ Pij < 1 
m
and  Σ  j=1 Pij=1 , (i,j= 1,2, … ,m) is the transition probability matrix in a state. 
6.12. Cellular utomaton Markov model 
A cellular automaton model is developed to investigate its utility in constructing 
scenarios of future urban land transformations (Clarke KC, Hoppen S, Gaydos L., 
1997). CA-Markov model combines cellular automata, Markov chain, multi-criteria, 
and multi-objective land allocation to predict land cover change over time (BEHERA, 
M.D., BORATE, S.N., PANDA, S.N. et al., 2012). It adds into the Markov model not 
only spatial contiguity but also the probable spatial transitions occurring in a particular 
area over time. MARKOV and CA_MARKOV modules in IDRISI are used to create 
transition probability and transition area matrix (Adhikari, S.; Southworth, J., 2012). 
A transition probability matrix is obtained by cross-tabulation of two images of 
different times. It determines the probability of a pixel in a land-use class to change 
into another class during that time (Sylvertown J, Hotlier S, Johnson J and Dale P, 
1992). On the other hand, a transition area matrix contains the number of pixels 
expected to change to a land-use class from another class during a period.  
 
 
 
110 
 
 
 
 
 
 
 
 
Chapter Seven 
 
 
 
 
 
 
 
 
 
 
 
 
 
111 
 
 
 
 
Demographic analysis, 
Urban population growth, Urban-
rural migration  
 
 
7.1. Population 
The population is a social entity with multiple contents and a type of social 
relations. It involves gender, age, actual structure, and various social-economic 
compositions and relations (Wei Li, Zhongyu Su, Pengcheng Guo, 2019).  The origins 
and consequences of urban population growth must be understood and evaluated 
towards realizing sustainable urban growth and sustainable cities (cliolu, 2016). Urban 
population growth in developing countries has been one of the most significant 
concerns that have brought considerable difficulties since the second half of the 
twentieth century (Mardiansjah, F.H., Rahayu, P., Rukmana, D., 2019). 
This chapter presents an overview concerning urban population growth, explains 
the importance of analyzing it, and explains it using the population prediction model.  
 
 
 
112 
 
7.2. Population growth rate  
Calculating Elasticity Rate of the population for Sari City, and define its place 
concerning the National and Regional Changes 
At the National level: 
Table 6 Iran’s population, Source: Analysed and classified by the author, 2021, and raw data from the (Statistical Center 
of Iran, 1956-2017). 
Decades 1956 1966 1976 1986 1996 2006 2016 
Iran’s 18500000 25789000 33709000 49445000 60055000 70495000 79926270 
population 
 
90000000
79926270
80000000
70495000
70000000
60055000
60000000
49445000
50000000
40000000 33709000
30000000 25789000
18500000
20000000
10000000
0
1956 1966 1976 1986 1996 2006 2016
Population of Iran
 
Figure 66 Iran’s population, Source: the column chart designed by the author, and the data from the (Statistical Center of 
Iran, 1956-2017). 
 
Table 7 Iran's urban and rural population changes, Source: Analysed and classified by the author, 2021, and the data 
from the (Statistical Center of Iran, 1956-2017). 
Decades 1956 1966 1976 1986 1996 2006 2016 
Urban population 6002121 9795810 15854680 26844561 36817789 48245057 59146847 
The percent of the population 32.44 37.98 47.04 54.29 61.31 68.44 74.01 
Growth in %  5.54 9.06 7.25 7.02 7.13 5.57 
Rural population 12497879 15993190 17854320 22600439 23237211 22249943 20779423 
Percent of the population 67.56 62.02 52.96 45.71 38.69 31.56 25.99 
 
113 
 
 
70000000
60000000
50000000
40000000
30000000
20000000
10000000
0
1956 1966 1976 1986 1996 2006 2016
Urban Population of Iran Rural Population of Iran
 
Figure 67 Iran’s urban and rural population. Source: the graph designed by the author, and the data from the (Statistical 
Center of Iran, 1956-2017). 
 
 
Table 8 The migration of urban or rural areas. Source: Analysed and classified by the author, 2021, and the data from the 
(Statistical Center of Iran, 1956-2017). 
Decades The rate of The migration The migration Precent of the Precent of the 
migration at the to the urban to the rural migration to the migration to the 
national level area area urban area rural area 
1976-1986 4816702 3447767 1368935 71.58 28.42 
1986-1996 8435865 5952076 2483789 70.56 29.44 
1996-2006 11783774 8715719 3068055 73.96 26.04 
2006-2016 10243815 8384934 1858881 81.85 18.15 
 
 
 
 
114 
 
 
Figure 68, The migration of urban or rural areas. Source: the column chart designed by the author, and the data from the 
(Statistical Center of Iran, 1956-2017). 
As presented in the above chart, the blue color shows the total migration at the 
national level. The red color indicates the total migration to the urban area, and the 
green color for the rural area. 
 
Figure 69, The urban-rural migration at the national level in percent. Source: the graph designed by the author, and the 
data from the (Statistical Center of Iran, 1956-2017). 
 
In Iran, the urban population growth is accompanied by the development of the 
urbanization process. On the one hand, based on the results of chapter eight, the 
number and areas of the Persian cities have increased. On the other hand, after the 
115 
 
executed statistical analysis, the find outs of this chapter have shown that Irans' 
population growth also grows the population of the urban areas due to the extreme 
migration from rural to the cities, which was started in the last decades.  The reasons 
for such trends are discussed in chapter eight, and this chapter has tried to discuss and 
present the demographic changes and analysis with the selected models to figure out 
what demographical changes happened during the last decades? How these changes 
happened? and why? Also, what is going to happen in the future? 
As shown in Table 7, about 67.56 percent of the population lived in the rural zones 
and 32.44 % in the urban zones in the 1956s. After six decades, in 2016, 
approximately 74.01 % of the population lived in urban areas and 25.99 % of the 
people in non-urban areas. According to the results illustrated in Figure 67, the graph 
shows gradual urban population growth, and the line goes up. And expected this urban 
population growth would be continued for the following decades. The most rate of 
urban population growth happened between the decades 1976 and 1986 Table 7.  
There is a significant relationship between the statistical results of urban population 
growth and the increase of migration from rural to urban. If we look at Table 7, 
besides the urban population growth, the rate of migration from rural to urban has 
increased sharply Table 8. For instance, about 11,783,774 million of the total urban 
populations of the country were the rural dwellers that were migrated to the urban 
zones between the decades 1996-2006. In other words, about 35,280,156 or 59.65% of 
Iran's urban population were the migrated people from the rural areas! 
 
 
 
 
 
 
 
116 
 
At the Regional level: 
Table 9 The total population of the Mazandaran metropolitan area. Source: Analysed and classified by the author, and 
the data from the (Statistical Center of Iran, 1956-2017). 
Decades 1956 1966 1976 1986 1996 2006 2016 
The population of the Mazandaran 
973964 1247102 1596565 2274862 2602008 2922432 3283582 
metropolitan area 
 
3500000
3000000
2500000
2000000
1500000
1000000
500000
0
1956 1966 1976 1986 1996 2006 2016
Population of the Mazandaran Province
 
Figure 70 The total population of Mazandaran. Source: the graph designed by the author 2021, and the data from the 
(Statistical Center of Iran, 1956-2017). 
 
Table 10 The population of the Mazandaran metropolitan area and rural area. Source: Analysed and classified by the 
author, and the data from the (Statistical Center of Iran, 1956-2017). 
Decades 1956 1966 1976 1986 1996 2006 2016 
The urban population of 
the Mazandaran 156329 301729 511787 897667 1223326 1554143 1936662 
metropolitan area 
The percent of the 
population 16.05% 24.19% 32.06% 39.46% 47.01% 53.18% 58.98% 
The rural Population of 
817635 945373 1084778 1377195 1378682 1368289 1346920 
Mazandaran 
The percent of the 83.95% 75.81% 67.94% 60.54% 52.99% 46.82% 41.02% 
population 
 
 
 
 
117 
 
Table 11 The changes in the growth of urban-rural population at the Sari city and district levels. Source: Analysed and 
classified by the author, and the data from the (Statistical Center of Iran, 1956-2017). 
1956 1966 1976 1986 1996 2006 2016 
Decades 
The total population of Sari district 129168 204982 262877 370515 422461 490830 504298 
The urban population of Sari district 27037 44547 70753 141020 207900 272000 352111 
The rural population of Sari district 102131 160435 192124 229495 214561 218830 152187 
The population of Sari city 27037 44547 70753 141020 195882 259413 347402 
 
 
Figure 71 The growth of populations in the urban and rural areas of the Mazandaran metropolitan area. Source: the 
graph designed by the author, and the data from the (Statistical Center of Iran, 1956-2017). 
 
 
Figure 72 The changes in the growth of urban-rural population at the Sari city and district levels Source: the graph 
designed by the author, and data from the (Statistical Center of Iran, 1956-2017). 
 
118 
 
Calculating the rates of population growth and changes for Sari city and 
compared to the national and regional levels 
Table 12 Calculating the rate of populations growth and changes at the national, regional, and local levels (by the author) 
1996- 2006-
Decades 1956-66 1966-76 1976-86 1986-96 
2006 2016 
Growth Growth Growth Growth Growth Growth 
The rate of growth 
in % in % in % in % in % in % 
Iran’s population  3.378 2.714 3.905 1.963 1.616 1.264 
Iran’s urban population 5.020 4.933 5.407 3.210 2.740 2.058 
Iran’s rural population 2.497 1.107 2.385 0.278 -0.433 -0.681 
The total population of the 
2.503 2.501 3.604 1.353 1.168 1.172 
Mazandaran metropoitan area 
The urban population of the 
6.797 5.426 5.780 3.144 2.422 2.225 
Mazandaran metropolitan area 
The urban population of Sari district 1.462 1.385 2.415 0.011 -0.076 -0.157 
Big cities' population of Mazandaran 
5.120 4.735 7.140 3.958 2.724 2.615 
metropolitan area 
The population of Sari city 4.798 4.569 5.967 3.100 2.458 2.195 
       
Change Change Change Change Change Change 
The rate of changes 
in % in % in % in % in % in % 
Iran’s population  - -19.636 43.875 -49.734 -17.692 -21.797 
Iran’s urban population - -1.742 9.613 -40.641 -14.632 -24.883 
Iran’s rural population - -55.665 115.487 -88.335 -255.697 -57.297 
The total population of the 
- -0.070 44.101 -62.467 -13.648 0.334 
Mazandaran metropolitan area 
The urban population of the 
- -20.169 6.522 -45.609 -22.945 -8.156 
Mazandaran metropolitan area 
The rural Population of this 
- -5.280 74.399 -99.553 -800.890 -107.933 
metropolitan area 
The urban population of Sari district - -7.519 50.796 -44.571 -31.178 -3.996 
Big cities' population of Mazandaran 
- -4.761 30.587 -48.050 -20.695 -10.705 
metropolitan area 
The population of Sari city - -7.519 50.796 -53.215 -14.721 4.028 
119 
 
 
Figure 73 The linear graph of the population changes at the national, regional, and local levels (by the author) 
 
 
Figure 74 The column chart of the population changes at the national, regional, and local levels (by the author) 
 
Since the 1921s, Iran's annual population growth rate was low for about 0.6% per 
year. Lack of health facilities was the main factor. And later, the 1925s, after the 
change of political system and foundation of the Pahlavi dynasty, consequently have 
120 
 
emerged considerable changes in all social, cultural, political, and economic sectors. 
Iran has started to move towards development gradually. The foundation of the 
Pahlavi dynasty, with many positive changes in Iran, also improving Iran's health 
facilities, political-economic stability is one of the main reasons for increased 
population growth. From 1957 to 1966, the government executed many development 
projects at the national level that positively changed living conditions, especially in 
the urban area. For more information, please see chapter nine. For example, the 
Family Planning projects for supporting Iranian families, constructing many new 
hospitals, or foundation of the first national education system that was free for all 
people, or for the first time foundation of national universities and university clinics 
had improved and enhanced living conditions for Iranian people. And also, for the 
first time in the history of this country, Reza Shah has provided recognition for 
women's rights to have more role in all sectors in the developing process of this 
country, which had increased women's employment officially. Finally, the cities 
became more populated than before Figure 72. 
According to the final results, especially Table 12, in this case, there is a significant 
relationship among the demographic changes at the national level and consequently at 
the regional and local levels. In 88.09 % of cases at all levels and periods, the same 
modifications happened with little tolerance Figure 73 -Table 12. For instance, 1986 
was one of the remarkable decades in the history of Iran's demographic changes 
because one of the highest rates of population surge had happened in this time at the 
national level.  
Because the revolution in 1979 had collapsed the Pahlavi dynasty and driven Iran 
into chaos and political instability. Three years later, Iraq used this political instability 
and invaded Iran, and this war lasted for eight years. At this time, the government had 
concerns about population growth and directly executed incentive policies to increase 
population growth, which led to an extremely high rate of 91.3. They are the main 
reasons for these enormous demographic changes Figure 74. 
121 
 
7.3. Elasticity analysis  
This study has applied elasticity analysis to know which life-history stages most 
impact on population growth. Sensitivity and elasticity are long-established, widely-
used instruments for pinpointing effective peculiar demographic rates in this process 
(Lee, 2016). Elasticity analysis is a manageable initial measure in clarifying essential 
issues in evolutionary and population science.  (Benton, Tim & Grant, Alastair, 2000). 
Elasticity analysis estimates the proportional change in population growth rate for a 
given change in a population rate parameter (Bart W. Durham and Gene R. Wilde, 
2004). 
This model is an index to estimate the percent of the urban population versus the 
total population. It means how much has increased or decreased the city's population 
as a case study for each one percent increase in the total population at the (national, 
regional, or local) levels in a specific period. 
This study used the following formula for estimating the elasticity rate of 
population growth: 
𝑌𝑢(𝑡, 𝑡 + 10)
𝐸(𝑡,𝑡+10) =  𝑟(𝑡, 𝑡 + 10)
E: is equal to the elasticity rate for a period  t,t+10 
Yu: the annual growth rate of urban population  
r: the annual growth rate of the total population  
 
 
 
 
 
 
122 
 
Calculating the elasticity rate of the population of Sari city compared to the 
national and regional levels 
 
Table 13 The elasticity rate of the populations at the national, regional, and local levels (by the author) 
Decades 1956-66 1966-76 1976-86 1986-96 1996- 2006-
2006 2016 
 Elasticit Elasticit Elasticit Elasticit Elasticit Elasticit
y rate y rate y rate y rate y rate y rate 
Iran’s urban population  1.4863 1.8173 1.3845 1.6350 1.6958 1.6289 
The population of the Mazandaran 0.7410 0.9214 0.9228 0.6890 0.7229 0.9275 
metropolitan area 
The urban population of the 2.7155 2.1694 1.6036 2.3240 2.0737 1.8982 
Mazandaran metropolitan area 
The urban population of Sari district 2.0457 1.8932 1.9812 2.9258 2.3319 2.2312 
Big Cities’ population of 1.9168 1.8269 1.6555 2.2915 2.1044 1.8729 
Mazandaran metropolitan area  
The population of Sari city 2.0457 1.8932 1.9812 2.4696 2.4389 2.5287 
 
 
 
Figure 75 The column chart of the population's elasticity rate at the national, regional, and local levels (by the author) 
123 
 
 
Figure 76 The linear graph of the changes in the elasticity rate of the populations at the national, regional, and local 
levels (by the author) 
 
First, this study has calculated the elasticity rate of the population at the national, 
regional, and local levels and then has tried to comparison the elasticity rate of Sari 
city with the other sectors. According to the results of as shown by Table 13, the ratio 
of changes in the population growth except in the 1986s for the different decades was 
negative. In the 1976s, about 0.476 percent of Sari's population growth rate had 
decreased for every one percent decrease in the national population growth rate. 
Meanwhile, this rate for the big cities of this Metropol was 0.751, and for the 
Metropol was 0.20. In 1986, the growth rate changed drastically and was 43.875% 
positive growth at the national level and 30.587% positive growth for Sari. It means, 
for every one percent increase in the national population growth rate, about 0.305% of 
Sari's population growth rate had increased. Sari city, in comparison with the other 
sector, not only was faced with the low changes but also in 2016 experienced positive 
changes. 
Unfortunately, the highest rate of these population changes refers to the rural area, 
especially at the regional levels. Except for the 1986s, the rate of dwellers has been 
decreased in this Metropol surprisingly. For example, for every one percent decrease 
124 
 
in the rural population growth at the national level, about 8.890 % of the rural 
population of this Metropol has decreased. 
The population of all big cities at the regional levels has been changed and 
decreased more than in Sari city. It represents the superiority of the city in comparison 
with the other big cities based on the results of Rank-Size Role that is illustrated in 
Chapter eight. 
7.4. The projections of the population growth 
Population predictions are 'what-if' scenarios to determine how the population will 
grow in the expectation (United States Census Bureau, 2017). These projections are 
essential to calculate the population's force on this planetoid and the communities' 
future well-being (Kaneda, Toshiko, 2014). Patterns of population growth take trends 
in social development and employ predictions into the prospect (Roser, 2019). These 
models use trend-based presumptions concerning how populations react to business, 
social and technological powers to determine how they influence fertility, mortality, 
net migration, and population growth (Office for national statistics, 2021). 
In this chapter, some prediction models for population change are provided 
included the Modified Exponential Model and the Linear Regression Model to predict 
the population growth in the next few years and decades. 
7.4.1. The results of the projected population growth at the national 
level 
The projection of the population changes in Iranian cities using the Modified 
Exponential Model 
According to Malthus' model, once population size exceeds available resources, 
population growth decreases dramatically. This accelerating growing population size 
is called "exponential growth," signifying that the population increases by a fixed rate 
each year (Zehnder, 2021). 
This type of growth can be represented by applying a mathematical function known 
as the exponential growth model: 
125 
 
𝑃 𝑛(𝑡+𝑛) = 𝑃(𝑡)(1 + 𝑟)  
𝑃(𝑡+𝑛): population in the year t+n (end of period) 
𝑃(𝑡): population in the year t (start of the period) 
𝑛: period considering (month, year, half of a year) 
r: the annual growth of population  
So that r (the annual growth of population) will be calculated by using the 
following formula: 
𝑛 𝑃(𝑡)
𝑟 = ( √ − 1) × 100 
𝑃.
In this model, the amount of population growth is addressed to the size of the 
current population. The proportion between the population growth and the total 
population is fixed (Mirnajaf Mossavi, Hassan Hekmatnia, 2011). 
 
Table 14 The projected population change in Iranian cities between 2016-2026 using the Modified Exponential Model at 
the national level (by the author) 
Iran’s urban The rate of The result of ME 
Decades 
population growth model 
1956 6002121 
  
1966 9795810 5.020374022 
 
1976 15854680 4.932909013 15987331 
1986 26844561 5.407104247 25661061 
1996 36817789 3.209610678 45452223 
2006 48245057 2.739988301 50496247 
2016 59146847 2.05819366 63219047 
2026 72512082 
  
 
126 
 
80000000
70000000
60000000
50000000
40000000 Population
ME model
30000000
20000000
10000000
0
1976 1986 1996 2006 2016 2026
 
Figure 77 The projected population growth in Iranian cities using the Modified Exponential Model at the national level 
(by the author) 
 
Projection of population for Iranian cities using the Linear Regression Model  
Linear regression enables you to make predictions on the data, and it is intuitive 
and easy to understand (Ognjanovski, 2018 ). 
Using the relationship between two variables, this model can calculate and estimate 
a variable by another variable. So that the variable Y changes concerning the time X. 
Therefore, can realize a linear relation between two groups of variables as follow: 
Y= ax+b 
Linear equation 
The amount of a and b is coefficients that can be calculated through the following 
formulas: 
∑ 𝑥𝑦
𝑎 =  
∑ 𝑥2
∑ 𝑦
𝑏 =  
𝑁
N: is the number of periods (Mirnajaf Mossavi, Hassan Hekmatnia, 2011). 
127 
 
Table 15 The projected population change in Iranian cities for the decades 2026 and 2036 using the Linear Regression 
Model at the national level (by the author) 
Iran’s 
The result of LR 
Decades urban x X^2 XY 
model 
population 
1956 6002121 -3 9 -18006363 
 
1966 9795810 -2 4 -19591620 
 
1976 15854680 -1 1 -15854680 
 
1986 26844561 0 0 0 
 
1996 36817789 1 1 36817789 
 
2006 48245057 2 4 96490114 
 
2016 59146847 3 9 177440541 
 
Sum 202706865 28 257295781 
  
2026 65714664 
    
2036 74903799 
    
Concerning the results of both models, Iran's urban population will be increased 
extremely high. As presented in the above tables, the urban population was 
59,146,847 in 2016, about 74.01% of the total population. The Modified Exponential 
Model has projected a continuation of urban population growth of approximately 
72,512,082 for the following years in 2026 Table 14. Besides, the Linear Regression 
Model has also predicted urban population growth for the following decades, about 
65,714,664 for 2026 and 74,903,799 people for 2036 Table 15. 
7.4.2. The results of the projected population growth in the 
Mazandaran metropolitan area 
The projection of the population changes in the Mazandaran metropolitan 
area using the Modified Exponential Model  
Table 16 The prediction of population change using the Modified Exponential Model for the Mazandaran metropolitan 
area (by the author) 
The population of the The rate of The result of ME 
Decades 
Mazandaran metropolitan area growth model 
1956 156329 
  
1966 301729 6.796679611 
 
1976 511787 5.425876327 582364 
1986 897667 5.779765762 868083 
1996 1223326 3.143697181 1574495 
2006 1554143 2.422383229 1667129 
2016 1936662 2.224803745 1974421 
2026 2413329 
  
128 
 
3000000
2500000
2000000
1500000 Population
ME model
1000000
500000
0
1976 1986 1996 2006 2016 2026
 
Figure 78 The predicted population growth of the Mazandaran metropolitan area for the years 2026 (by the author) 
 
Prediction of population based on the Linear Regression Model  
Table 17 The predicted changes in the population of the Mazandaran metropolitan area using the Linear Regression 
Model for the decades 2026-2036 (by the author) 
The population of the Mazandaran metropolitan area 
The result of LR 
Decades y x X^2 XY 
model 
1956 156329 -3 9 -468987 
 
1966 301729 -2 4 -603458 
 
1976 511787 -1 1 -511787 
 
1986 897667 0 0 0 
 
1996 1223326 1 1 1223326 
 
2006 1554143 2 4 3108286 
 
2016 1936662 3 9 5809986 
 
Sum 6581643 28 8557366 
  
2026 2162716 
    
2036 2468336 
    
 
 
Concerning the results of both models, the urban population of this metropolitan 
area will be increased considerably high. As presented in the above tables, the urban 
population was 1,974,421in 2016, about 58.98% of the total population. The Modified 
129 
 
Exponential Model has projected a continuation of urban population growth about 
2,413,329 for the following years in 2026 Table 16. 
Besides, the Linear Regression Model has also predicted urban population growth 
for the following decades, about 2,162,716 for 2026 and 2,468,336 people for 2036 
Table 17. 
7.4.3. The results of the projected population growth at the local level 
The projection of the population changes in the city of Sari using the Modified 
Exponential Model  
Table 18 The projected changes in the population of Sari city between 2016-2026 using the Modified Exponential Model  
(by the author) 
The population The rate of The result of ME 
Decades 
of Sari city  growth model 
1956 27037 
  
1966 44547 5.120155849 
 
1976 70753 4.735193573 73397 
1986 141020 7.140479358 112375 
1996 195882 3.340695936 281071 
2006 259413 2.848916461 272087 
2016 347402 2.963680387 343549 
2026 465,235 
  
 
500000
450000
400000
350000
300000
250000 Population
200000 ME model
150000
100000
50000
0
1976 1986 1996 2006 2016 2026
 
Figure 79 The predicted population growth of Sari city between 2016-2026 (by the author) 
 
130 
 
Prediction of the population of Sari city using the Linear Regression Model  
Table 19 The predicted population growth in Sari city using the Linear Regression Model for the decades 2026-2036 (by 
the author) 
The population of Sari City 
The result of LR 
Decades y x X^2 XY 
model 
1956 27037 -3 9 -81111 
 
1966 44547 -2 4 -89094 
 
1976 70753 -1 1 -70753 
 
1986 141020 0 0 0 
 
1996 195882 1 1 195882 
 
2006 259413 2 4 518826 
 
2016 347402 3 9 1042206 
 
Sum 1086054 28 1515956 
  
2026 - - - - 371716 
2036 - - - - 425857 
 
 
Concerning the results of both models, the urban population of this metropolitan 
area will be increased considerably high. As presented in the above tables, the urban 
population was 347,402 in 2016, about 17.93% of the total urban population in this 
metropolitan area. The Modified Exponential Model has projected a continuation of 
urban population growth of about 465,235 for the following years in 2026 Table 18. 
Besides, the Linear Regression Model has also predicted urban population growth 
for the following decades, about 371,716 for 2026 and 425,857 people for 2036 Table 
19.  
 
 
 
 
 
131 
 
 
 
 
 
 
 
 
Chapter Eight 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
132 
 
 
 
 
 
Economic Sector 
 
 
Flix-Auerbach is a German geographer and, in 1913, has provided the Rank-Size 
Rule to analyze the relationship between the size and place of cities (Mirnajaf 
Mossavi, Hassan Hekmatnia, 2011). And later in the 1940s, George Zipf identified a 
curious regularity in the distribution of cities of varying sizes; if cities were ranked 
from largest to smallest populations, then 
𝑃1
𝑃𝑟 =  𝑅𝑏
P1: the population of the largest city or town,  
PR: the population of the smallest city by rank, 
b: a coefficient that must be established through empirical observation for each 
investigation. The greater the value of b, the steeper the slope, and the greater the 
primacy of the largest city or town. 
George Zipf defines the above formula in a logarithm form as follow: 
𝐿𝑜𝑔𝑃𝑟 = 𝐿𝑜𝑔𝑃1 − 𝑏𝐿𝑜𝑔𝑅 
𝑃
𝐿𝑜𝑔 1
𝑃
𝑏 = 𝑟  
𝐿𝑜𝑔𝑅
The contribution of rank-size rule in urban regional planning: 
133 
 
 
 It helps in the interpretation of the relationship between rank and population of 
settlements. 
 It helps in analyzing the settlement networks. 
 It explains settlements concerning economic activities as an increase in 
activities increases the size of population. 
 It explains the imbalance between the settlements due to rapid growth in 
population or activities (Kumar V. , 2017). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
134 
 
 
8.1. The results of Rank-Size Rule, Zipf's law for the 
decade 1986 
Table 20 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of Mazandaran metropolitan 
area between decades 1976- 1986, Iran  (by the author) 
Class Population Regression Model 
Real 
Of Row Cities Rank Zipf's law surplus or population 
decline LogR=x LogR=y Cities 
1 Sari 141020 1 141020 0 0 5.14928 
2 Amol 118242 2 70510 47732 0.30103 5.07277 
B2 
3 Babol 115320 3 47007 68313 0.47712 5.0619 
4 Ghaemshahr 109288 4 35255 74033 0.60206 5.03857 
B1 5 Behshahr 52461 5 28204 24257 0.69897 4.71984 
6 Tonekabon 29380 6 23503 5877 0.77815 4.46805 
7 Challos 29308 7 20146 9162 0.8451 4.46699 
8 Babolsar 28589 8 17628 10962 0.90309 4.4562 
9 Nooshahr 28216 9 15669 12547 0.95424 4.4505 
10 Ramsar 25352 10 14102 11250 1 4.40401 
11 Neka 23604 11 12820 10784 1.04139 4.37299 
12 Freydonkenar 20997 12 11752 9245 1.07918 4.32216 
13 Juybar 18942 13 10848 8094 1.11394 4.27743 
14 Amirkolah 18295 14 10073 8222 1.14613 4.26233 
15 Galogah 18073 15 9401 8672 1.17609 4.25703 
16 Katalem Sadatshahr 13509 16 8814 4695 1.20412 4.13062 
A 17 Nor 13055 17 8295 4760 1.23045 4.11578 
18 Mahmoodabad 11856 18 7834 4022 1.25527 4.07394 
19 Zirab 9595 19 7422 2173 1.27875 3.98204 
20 Rostamkolah 9220 20 7051 2169 1.30103 3.96473 
21 Abbasabad 8169 21 6715 1454 1.32222 3.91217 
22 Khoramabad 8154 22 6410 1744 1.34242 3.91137 
23 Shirgah 7452 23 6131 1321 1.36173 3.87227 
24 Salmanshahr 7087 24 5876 1211 1.38021 3.85046 
25 Polsefeed 6423 25 5641 782 1.39794 3.80774 
26 Nashtarood 4760 29 4863 -103 1.41497 3.67761 
27 Kelarabad 4267 33 4273 -6 1.43136 3.63012 
28 Royan 4035 34 4148 -113 1.44716 3.60584 
135 
 
 
29 Kelardasht 4030 35 4029 1 1.4624 3.60531 
30 Marzanabad 3889 36 3917 -28 1.47712 3.58984 
31 Keeyakolah 2964 48 2938 26 1.49136 3.47188 
32 Rineh-e-Larijan 1225 115 1226 -1 1.50515 3.08814 
33 Alasht 890 158 893 -3 1.51851 2.94939 
  SUM 897667 564413 333254   
 
  
 
Figure 80, The imbalance between the actual size of the population with the ideal size of the population of cities in the 
Mazandaran metropolitan area considering the results of Zip's law; between 1976- 1986, Iran (by the author) 
 
 
 
 
 
 
136 
 
 
8.2. The results of Regression model for the decade 
1986 
The calculation of Rank-Size Rule using the Regression Model 
 
Figure 81 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of Rank-Size 
Rule between 1976- 1986, Iran (by the author) 
Best-fit values     
Slope  -1.336 ± 0.09685  
Y-intercept  5.618 ± 0.1141  
X-intercept  4.204  
1/Slope  -0.7483  
95% Confidence Intervals     
Slope  -1.534 to -1.139  
Y-intercept  5.385 to 5.850  
X-intercept  3.803 to 4.742  
   
Goodness of Fit     
R square  0.8600  
Sy.x  0.2042  
   
Is slope significantly non-
   
zero?  
F  190.4  
DFn,DFd  1,31  
P Value  < 0.0001  
Deviation from horizontal?  Significant  
   
Data     
Number of XY pairs  33  
Equation  Y = -1.336*X + 5.618  
137 
 
 
In Iran, based on the National Spatial Plan, the cities are classified into five groups 
according to the rate of population Table 21: 
 
Table 21 The calcification of urban area based on the population in Iran (by the author) 
Classes Urban Groups Population 
A Small cities less than 50000 
B1 Medium-sized cities (small-class) 50000 to 99999 
B2 Medium-sized cities (big-class) 100000 to 249999 
C1 Big cities (Medium-class) 250000 to499999 
C2 Big and very big Cities 500000 to 2000000 
 
In the first row of Table 20, this thesis has defined the rank of cities according to 
the annual data. And in the second row is listed the cities' name and their population in 
the next row. After that, in the next raw, we are considering the result of the Rank-
Size Rule. Then, in the next row, we can see the results of Zipf's law and the ideal 
population size for the cities. According to Zipf's law, the next row shows the 
difference between the actual and perfect population size.  
As showed in Table 20, the numbers of cities in the Mazandaran metropolitan area 
were about 33, with 897,667 dwellers. The outcomes of the model show four cities 
have been placed in medium-sized cities (big class), one city in medium-sized (small-
class), and the rest have been placed in class A. About 53.90% of the total urban 
population in class B2, 5.85% of people in class B1, and 40.25% in small cities Figure 
82.  
 
Figure 82 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area (by the 
author) 
138 
 
 
Concerning the result of Zipf's law in Table 20, the measured population size for 
the urban area is about 564413, but statistics show the cities had 897667population. 
This metropolitan's urban system faced a surplus of almost 333254 people.  In other 
words, there is a considerable imbalance between the rank of cities and the size of the 
population. The concentration of 53.90% of the people in four cities (class C1) 
explains the growth of centralization in this region. Economic, social, and political 
factors have played a significant role in intensifying such unequal regional-spatial 
distribution.  As shown in the above graph Figure 80, the cities with ranks 1 to 4 have 
significant heterogeneity between the size of the actual population and Zipf's law with 
the highest distance between the two graphs on the column chart Figure 80. Also, this 
imbalance was continued between the cities with ranks 5 to 19. But the distance 
between the graphs is closer than the cities with upper ranks.  
In addition to the Rank-Size rule, this study used the regression model for further 
analysis and the results represented in Figure 81. Based on this model's law, if the 
slope of b is negative or (b<1), it means there is no balance. Unfortunately, for these 
decades, the slope is -1.336, therefore clearly representing unbalance between cities 
rank and population size.  
As shown in Figure 81, the logarithmic distribution of population is presented 
vertically, and the logarithmic distribution of cities ranks horizontally. The slope line 
goes down, and the distance between points of the four bigger cities is too much than 
the other size of cities. Just for the cities between ranks 20 to 48, the imbalance rate is 
less than other cities. Moreover, the imbalance and distance have risen dramatically 
concerning the calculated ranks for the last two cities.  
 
 
 
 
139 
 
 
8.3. The results of Rank-Size Rule, Zipf's law for the 
decade 1996 
Table 22 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 1986- 1996, Iran (by the author) 
Class Population Regression Model 
Real Zipf's 
Of Row Cities Rank surplus or population law 
Cities decline LogR=x LogR=y 
1  Sari 195882 1 195882 0 0 5.291995 
B2 
2  Amol 159092 2 97941 61151 0.30103 5.201648 
3  Babol 158346 3 65294 93052 0.477121 5.199607 
 
4  Ghaemshahr 143286 4 48971 94316 0.60206 5.156204 
B1 5  Behshar 72067 5 39176 32891 0.69897 4.857736 
6  Challos 41403 6 32647 8756 0.778151 4.617032 
7  Babolsar 38644 7 27983 10661 0.845098 4.587082 
8  Neka 35208 8 24485 10723 0.90309 4.546641 
9  Nooshahr 35133 9 21765 13368 0.954243 4.545715 
10  Tonekabon 33650 10 19588 14062 1 4.526985 
11  Ramsar 28954 11 17807 11147 1.041393 4.461709 
12  Freydonkenar 27976 12 16324 11653 1.079181 4.446786 
13  Jouybar 23909 13 15068 8841 1.113943 4.378561 
14  Amirkolah 21280 14 13992 7288 1.146128 4.327972 
15  Mahmoodabad 20054 15 13059 6995 1.176091 4.302201 
16  Galogah 18073 16 12243 5830 1.20412 4.25703 
A 17  Zirab 17196 17 11522 5674 1.230449 4.235427 
18  Noor 16808 18 10882 5926 1.255273 4.225516 
Katalem 
19 16239 19 10310 5929 1.278754 4.210559 
 sadatshahr
20  Rostamkolah 10773 20 9794 979 1.30103 4.032337 
21  Kelardasht 10482 21 9328 1154 1.322219 4.020444 
22  Khoramabad 9881 22 8904 977 1.342423 3.994801 
23  Shirgah 9546 23 8517 1029 1.361728 3.979821 
24  Abbasabad 9384 24 8162 1222 1.380211 3.972388 
25  Salmanshahr 8302 25 7835 467 1.39794 3.919183 
26  Sorak 8236 26 7534 702 1.414973 3.915716 
27  Chamestan 7926 27 7255 671 1.431364 3.899054 
140 
 
 
28  Polsefeed 7648 28 6996 652 1.447158 3.883548 
29  Keeyahkolah 6810 29 6755 55 1.462398 3.833147 
30  Marzanabad 6488 30 6529 -41 1.477121 3.812111 
31  Royan 5592 35 5597 -5 1.491362 3.747567 
32  Kelarabad 4973 39 5023 -50 1.50515 3.696618 
33  Nashtarood 4770 41 4778 -8 1.518514 3.678518 
34  Keyahsar 3782 51 3841 -59 1.531479 3.577722 
35  Sorkhrood 3772 52 3767 5 1.544068 3.576572 
Rineh-e-
36 1337 147 1333 4 1.556303 3.126131 
 Larijan
37  Alasht 424 462 424 0 1.568202 2.627366 
  SUM 1223326 807307 416019  
  
 
 
 
Figure 83 The imbalance between the actual size of the population with the ideal size of the population of cities in 
the Mazandaran metropolitan area considering the results of Zip's law; between 1986- 1996, Iran (by the author) 
 
 
141 
 
 
8.4. The results of Regression model for the decade 
1996 
The calculation of Rank-Size Rule using Regression Model 
 
Figure 84 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of Rank-Size 
Rule between 1986- 1996, Iran (by the author) 
Best-fit values     
Slope  -1.363 ± 0.1021  
Y-intercept  5.770 ± 0.1250  
X-intercept  4.232  
1/Slope  -0.7335  
95% Confidence Intervals     
Slope  -1.571 to -1.156  
Y-intercept  5.516 to 6.024  
X-intercept  3.824 to 4.786  
   
Goodness of Fit     
R square  0.8358  
Sy.x  0.2309  
   
Is slope significantly non-zero?     
F  178.2  
DFn,DFd  1,35  
P Value  < 0.0001  
Deviation from horizontal?  Significant  
   
Data     
Number of XY pairs  37  
Y = -1.363*X + 
Equation  
5.770  
142 
 
 
Results of the model for this decade show a continuation of heterogeneity and 
imbalance that was started from the last decade or decades, without remarkable 
changes during this decade Table 22. The number and size of cities have grown 
numerically from 33 cities to 37, and population from 897667 to 1,223,326.  
The expected urban population size for this decade, concerning the results of Zipf's 
law, is about 807307 dwellers Table 22. But in fact, statistics show that the cities were 
populated with 1,223,326 dwellers and faced a surplus of population. About 416019 
people were settled over the capacities of these cities. According to the results, 54% of 
the population concentrated in class B2, 6% in class B1, and 40% in class A Figure 
85. 
 
Figure 85 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area (by the 
author) 
 
As illustrated in graph Figure 83, there is substantial heterogeneity between the size 
of the population in the cities with ranks 1 to 4 compared to the results of Zipf's law.  
This problem imposed a big gap or distance between the two graphs on the column 
chart. Also, the imbalance for the cities with ranks between 5 to 19 is lower than the 
cities with upper ranks. Based on the results of the Regression Model, unfortunately, 
the slope rate for this decade is -1.363, a little bit more than before.  
143 
 
 
As shown in Figure 84, the logarithmic distribution of population is presented 
vertically, and the logarithmic distribution of the cities ranks horizontally. The 
direction of the slop line downward and distance between points for the first four 
larger cities is too much compared to the other cities. And for other ranks from 5 up to 
21 is lower. Just for this size of cities with ranks between 22-52, the imbalance rate is 
less than other cities. Moreover, for the last two cities with ranks 147 and 462, the 
distance rate concerning the ranks has risen dramatically.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
144 
 
 
8.5. The results of Rank-Size Rule, Zipf's law for the 
decade 2006 
Table 23 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 1996- 2006, Iran (by the author) 
Class Population Regression Model 
Real Zipf's 
Of Row Cities Rank surplus or population law 
decline LogR=x LogR=y Cities 
1  Sari 261293 1 261293 0 0 5.417128 
2  Amol 201335 2 130647 70689 0.30103 5.303919 
B2 
3  Babol 199698 3 87098 112600 0.477121 5.300374 
4  Ghaemshahr 174768 4 65323 109445 0.60206 5.242462 
5  Behshar 84117 5 52259 31858 0.69897 4.924884 
B1 
6 Babolsar 50032 6 43549 6483 0.778151 4.699248 
7 Neka 46291 7 37328 8963 0.845098 4.665497 
8 Challos 45625 8 32662 12963 0.90309 4.659203 
9 Tonekabon 43842 9 29033 14809 0.954243 4.64189 
10 Nooshahr 42175 10 26129 16046 1 4.625055 
11 Freydonkenar 34496 11 23754 10742 1.041393 4.537769 
12 Ramsar 32085 12 21774 10311 1.079181 4.506302 
13 Mahmoodabad 27748 13 20099 7649 1.113943 4.443232 
14 Jouybar 27211 14 18664 8547 1.146128 4.434745 
15 Amirkolah 25291 15 17420 7871 1.176091 4.402966 
16 Noor 22491 16 16331 6160 1.20412 4.352009 
17 Galogah 18727 17 15370 3357 1.230449 4.272468 
A 
18 Zirab 18388 18 14516 3872 1.255273 4.264534 
Katalem 
19 17955 19 13752 4203 1.278754 4.254185 
sadatshahr 
20 Kelardasht 11999 20 13065 -1066 1.30103 4.079145 
21 Rostamkolah 11408 21 12443 -1035 1.322219 4.05721 
22 Abbasabad 11278 22 11877 -599 1.342423 4.052232 
23 Khalilshahr 10126 23 11361 -1235 1.361728 4.005438 
24 Khoramabad 9945 24 10887 -942 1.380211 3.997605 
25 Salmanshahr 9664 25 10452 -788 1.39794 3.985157 
26 Chamestan 9499 26 10050 -551 1.414973 3.977678 
27 Sorak 8822 27 9678 -856 1.431364 3.945567 
145 
 
 
28 Polsefeed 8708 28 9332 -624 1.447158 3.939918 
29 Shirgah 8611 29 9010 -399 1.462398 3.935054 
30 Keyahkolah 7472 34 7685 -213 1.477121 3.873437 
31 Mazanabad 7102 36 7258 -156 1.491362 3.851381 
32 Gatab 6956 37 7062 -106 1.50515 3.84236 
33 Izadshahr 6888 38 6876 12 1.518514 3.838093 
34 Bahnamir 6848 39 6700 148 1.531479 3.835564 
35 Sorkhrood 6620 40 6532 88 1.544068 3.820858 
36 Royan 6351 41 6373 -22 1.556303 3.802842 
37 Nashtarood 5967 44 5938 29 1.568202 3.775756 
38 Kelarabad 5457 47 5559 -102 1.579784 3.736954 
39 Keyahsar 3672 71 3680 -8 1.591065 3.564903 
40 Kallehbast 3561 73 3579 -18 1.60206 3.551572 
41 Khoshroodpey 3022 86 3038 -16 1.612784 3.480294 
42 Galogah-e-Babol 2519 103 2537 -18 1.623249 3.401228 
43 Koheekheyl 1950 134 1950 0 1.633468 3.290035 
44 Baladeh 1340 195 1340 0 1.643453 3.127105 
45 Rineh-e-Larijan 1213 215 1215 -2 1.653213 3.083861 
46 Dabodasht 1096 238 1098 -2 1.662758 3.039811 
47 Alasht 984 265 986 -2 1.672098 2.992995 
48 Marzikolah 525 498 525 0 1.681241 2.720159 
49 Zargarmahalleh 425 614 426 -1 1.690196 2.628389 
50 Gazanak 362 722 362 0 1.69897 2.558709 
51 Farrim 185 1412 185 0 1.70757 2.267172 
  SUM 1554143 1116058 438085 
   
 
 
 
146 
 
 
 
Figure 86 The imbalance between the actual size of the population with the ideal size of the population of cities in the 
Mazandaran metropolitan area considering the results of Zip's law; between 1996- 2006, Iran (by the author) 
 
8.6. The results of Regression model for the decade 
2006 
The calculation of Rank-Size Rule using the Regression Model 
 
 
Figure 87 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of Rank-Size 
Rule between 1996- 2006, Iran (by the author) 
 
147 
 
 
Best-fit values     
Slope  -1.660 ± 0.1138  
Y-intercept  6.135 ± 0.1541  
X-intercept  3.695  
1/Slope  -0.6023  
   
95% Confidence Intervals     
Slope  -1.889 to -1.431  
Y-intercept  5.826 to 6.445  
X-intercept  3.400 to 4.083  
   
Goodness of Fit     
R square  0.8128  
Sy.x  0.3113  
   
Is slope significantly non-zero?     
F  212.7  
DFn,DFd  1,49  
P Value  < 0.0001  
Deviation from horizontal?  Significant  
   
Data     
Number of XY pairs  51  
Y = -1.660*X + 
Equation  
6.135 
That decade coincided with the entry into the 21st century, and the urban system of 
this metropolitan area faced dramatic changes in the number and size of cities and 
population. According to the model results, as shown in the above table Table 23, 
numbers of cities in the Mazandaran metropolitan area have increased from 37 to 51 
significantly. The size of the population has been grown from 1,223,326 in 1996 to 
1554143 in 2006. Results of models for this decade show the continuation of 
heterogeneity and imbalance that started from the last decades, accompanied by 
remarkable changes in Table 23. The numbers and size of cities have grown 
numerically from 33 cities to 51, and increasing population from 1,223,326 to 
1,554,143. 
Concerning the results of Zipf's law, the predicted urban population size for this 
decade is about 1,116,058 dwellers Table 23. But statistics indicate that the cities were 
148 
 
 
populated with approximately 1,554,143 dwellers and faced a surplus of population. It 
means about 438085 dwellers over the capacities of the cities. According to the 
results, 53.86% of the population concentrated in class B2, 8.63% in class B1, and 
37.71% in class A Figure 88. For the first time in this region, two cities have been 
placed in class B. The population size of class B2 has increased from 656606 in 1996 
to 837094 in 2006. 
 
Figure 88 The percent of the spatial distribution of population in the cities of the Mazandaran metropolitan area (by the 
author) 
As illustrated in Figure 86, the model shows the continuation of a sharp imbalance 
from the past decades between the size of population among the cities.  Such 
heterogeneity has generated a big gap between the classes B2, B1, and A. Also, from 
the cities with ranks 5 to 19, we observed a continuation of this imbalance trend, but 
the distance between the graphs is closer than the cities with upper ranks 1 to 4.  
According to the regression model results, in this decade, the rate of the slope line 
is -1.660, the highest rate that was never seen before.  
Figure 8 presents a logarithmic distribution of the population vertically and a 
logarithmic distribution of the cities' ranks horizontally. The slope of the line is down, 
and the distance between points for the six superior cities is more than the cities with 
ranks 7 to 29. Just for these groups of cities with ranks 34 to 47, the imbalance rate is 
less than other cities. Moreover, the cities with ranks 71 to 1412 observed a dramatic 
imbalance. 
149 
 
 
8.7. The Rank-Size Rule, Zipf's law for the decade 2016 
Table 24 The result of the Rank-Size Rule, Zipf's law, and Regression Model for the cities of the Mazandaran 
metropolitan area between 2006- 2016, Iran (by the author) 
Class Population Regression Model 
Real 
Of Row Cities Rank Zipf's law surplus or population 
decline LogR=x LogR=y Cities 
1  Sari 347402 1 347402 0 0 5.540832 
C1 
2  Amol 250217 2 173701 76516 0.30103 5.398317 
3  Babol  237528 3 115801 121727 0.477121 5.375715 
B2 
4  Ghaemshahr 204953 4 86851 118103 0.60206 5.311654 
5  Behshar 94702 5 69480 25222 0.69897 4.976359 
6  Challos 65196 6 57900 7296 0.778151 4.814221 
B1 7  Neka 60991 7 49629 11362 0.845098 4.785266 
8  Babolsar 59966 8 43425 16541 0.90309 4.777905 
9  Tonekabon 55434 9 38600 16834 0.954243 4.743776 
10  Noshahr 49403 10 34740 14663 1 4.693753 
11  Freydonkenar 38154 11 31582 6572 1.041393 4.58154 
12  Ramsar 35997 12 28950 7047 1.079181 4.556266 
13  Juybar 32924 13 26723 6201 1.113943 4.517513 
14  Mahmoodabad 31844 14 24814 7030 1.146128 4.503028 
15  Amirkolah 30478 15 23160 7318 1.176091 4.483986 
16  Noor 26947 16 21713 5234 1.20412 4.43051 
17  Galogah 21352 17 20435 917 1.230449 4.329439 
18  Katalem Sadatshahr 20716 18 19300 1416 1.255273 4.316306 
19  Zirab 16191 22 15791 400 1.278754 4.209274 
A 
20  Abbasabad 13482 26 13362 120 1.30103 4.129754 
21  Kelardasht 13401 27 12867 534 1.322219 4.127137 
22  Rostamkolah 11686 30 11580 106 1.342423 4.067666 
23  Khorramabad 11542 31 11207 335 1.361728 4.062281 
24  Shirood 11377 31 11207 170 1.380211 4.056028 
25  Chamestan 11194 32 10856 338 1.39794 4.048985 
26  Khalilshahr 11032 33 10527 505 1.414973 4.042654 
27  Hachirud 10398 34 10218 180 1.431364 4.01695 
28  Arrateh 10327 35 9926 401 1.447158 4.013974 
29  Salmanshahr 9656 36 9650 6 1.462398 3.984797 
150 
 
 
30  Sorrak 9208 38 9142 66 1.477121 3.964165 
31  Shirgah 8671 40 8685 -14 1.491362 3.938069 
32  Polsefeed 8294 42 8271 23 1.50515 3.918764 
33  Keyahkolah 8040 43 8079 -39 1.518514 3.905256 
34  Bahnamir 7906 44 7896 11 1.531479 3.897957 
35  Hadishahr 7889 45 7720 169 1.544068 3.897022 
36  Royan 7731 45 7720 11 1.556303 3.888236 
37  Izadshahr 7439 47 7392 47 1.568202 3.871515 
38  Gatab 7374 48 7238 136 1.579784 3.867703 
39  Galogahbabol 6908 50 6948 -40 1.591065 3.839352 
40  Sorkhrood 6699 52 6681 18 1.60206 3.82601 
41  Marzanabad 6698 53 6555 143 1.612784 3.825945 
42  Nashtarood 6394 54 6433 -39 1.623249 3.805773 
43  Kelarabad 6267 55 6316 -49 1.633468 3.79706 
44  Emamzadehabdollah 5768 60 5790 -22 1.643453 3.761025 
45  Khoshroodpey 5742 77 5695 47 1.662758 3.653116 
46 Ejbarkollah 4499 81 4512 -13 1.653213 3.759063 
47  Zargarmahalleh 3991 87 3993 -2 1.672098 3.601082 
48  Keyhsar 3384 103 3373 11 1.681241 3.52943 
49  Pul 3150 110 3158 -8 1.690196 3.498311 
50  Kojur 3120 111 3130 -10 1.69897 3.494155 
51  Marzikolah 2710 128 2714 -4 1.70757 3.432969 
52  Koheekheyl 2242 155 2241 1 1.716003 3.350636 
53 Farahabad 2217 157 2213 4 1.724276 3.345766 
54  Dabodasht 1758 198 1755 3 1.732394 3.245019 
55  Alasht 1193 291 1194 -1 1.740363 3.07664 
56  Rineh-e-Larijan 982 354 981 1 1.748188 2.992111 
57  Baladeh 970 358 970 0 1.755875 2.986772 
58  Paeenhollar 956 363 957 -1 1.763428 2.980458 
59  Farim 369 941 369 0 1.770852 2.567026 
60  Gazannak 319 1089 319 0 1.778151 2.503791 
  SUM 1943378 1489837 453543 
   
  
 
151 
 
 
 
Figure 89 The imbalance between the actual size of the population with the ideal size of the population of cities in 
the Mazandaran metropolitan area considering the results of Zip's law; between 2006- 2016, Iran (by the author) 
 
8.8. The Regression model for the decade 2016 
The calculation of Rank-Size Rule using the Regression Model 
 
Figure 90 The logarithmic distribution of cities in the Mazandaran metropolitan area considering the rsults of Rank-Size 
Rule between 2006- 2016, Iran (by the author) 
152 
 
 
Best-fit values     
Slope  -1.551 ± 0.07939  
Y-intercept  6.134 ± 0.1127  
X-intercept  3.953  
1/Slope  -0.6445  
   
95% Confidence Intervals     
Slope  -1.710 to -1.393  
Y-intercept  5.908 to 6.359  
X-intercept  3.710 to 4.252  
   
Goodness of Fit     
R square  0.8682  
Sy.x  0.2386  
   
Is slope significantly non-zero?    
F  381.9  
DFn,DFd  1,58  
P Value  < 0.0001  
Deviation from horizontal?  Significant  
   
Data     
Number of XY pairs  60  
Equation  Y = -1.551*X + 6.134  
 
The outcomes of data analysis represent this decade more distinctive than others. 
For the first time emerged two big cities, and the new class C1 added to the class of 
cities in this metropolitan area with remarkable population size. At the end of 2006 
were four first cities in class B2, and today the cities of this class are divided into the 
two different classes B2 and C1 (Big Cities). Surprisingly, today we have five cities in 
class B2, which was never seen before Table 24.  
According to the above model results, as shown in Table 24, the numbers of cities 
in this metropolitan area have increased from 51 at the beginning of the decade to 60 
cities at the end of this decade significantly. The size of the population has risen 
rapidly from 1554143 in 2006 to 1,943,378 in 2016. The results show a continual 
growth of heterogeneity and imbalance in the size and rank of cities.  
153 
 
 
Concerning the results of Zipf's law, the urban population size for this decade is in 
this metropolitan area about 1,489,837 dwellers Table 24. But statistics show that the 
cities were populated with 1,943,378 dwellers and faced a surplus of population 
considerably. It means 453541 people were settled over the capacities of the cities. As 
shown in the pie chart Figure 91, 31% population of this metropolitan area dropped in 
the two first cities in class C1. And surprisingly, the second place belongs to the cities 
of class B2 with 23% of the population. Also, 17% of the population lives in class B1. 
The last place belongs to class A with 29% population of the Metropol.  
 
Figure 91 The percent of the spatial distribution of populations in the cities of the Mazandaran metropolitan area  (by the 
author) 
Table 25 Classifying the cities of the Mazandaran metropolitan area considering the population  (by the author) 
 Class C1 Class B2 Class B1 Class A Sum 
The population in percent 30.75% 22.77% 17.30% 29.18% 100 
Numbers of Cities and 2 2 5 51 60 
Towns 
 
As illustrated by the graphs on the column chart, Figure 89, we observe a gradual 
increase in the gap between the size of population and rank of cities concerning the 
results of Zipf's law compared with the statistical data.   
154 
 
 
As shown in the results, we face a polarized and centralized form of urbanization in 
this area, and urban hierarchies have no balance. 31% of the population live in the first 
two biggest cities of class C1, 23% live in two cities of class B2, 17% live in five 
cities from class B1, and 29% live in 51 cities of class A Table 25. 
According to the results of the regression model, unfortunately, the rate of the line 
of the slope is -1.55for this decade, which is about 5% lower than the last decade, but 
it is not a considerable difference or a remarkable change (see Figure 90). This graph 
presents the logarithmic distribution of the size of the population vertically and also a 
logarithmic distribution of the rank of the cities horizontally. The slope of the line is 
sinking, and the distance between the points for the nine superior cities became more 
than the other cities, surprisingly. And for the cities in class A between the ranks 10 to 
55, the imbalance degree is less than other cities. Moreover, for the cities with ranks 
60 to 1089, the model shows a drastic difference in terms of size and status compared 
with the cities class C1. 
 
Table 26 Number of cities in the Mazandaran metropolitan area from 1956 to 2016, Iran (by the author) 
 Decades 1956 1966 1976 1986 1996 2006 2016 
Numbers of cities and towns 19 16 22 33 35 51 60 
Numbers of added or decreased towns  -3 +6 +11 +2 +16 +9 
 
 
Figure 92 Numeric growth of cities in the Mazandaran metropolitan area from 1956 to 2016 (by the author) 
155 
 
 
Table 27 The proportion of the numbers of cities and size of the population to the total ratio, 1956-2016 (by the author) 
Decades 1956 1966 1976 1986 1996 2006 2016 Sum 
The proportion of the 
numbers of cities to the 19 16 22 33 35 51 60 60 
total proportion 
The size of urban 
population to the total 156329 301729 511787 897667 1223326 1554143 1943378 1943378 
proportion 
The proportion of the 
numbers of cities to the 32% 27% 37% 55% 58% 85% 100% 
total proportion in % 
 
The size of urban 
population to the total 8% 16% 26% 46% 63% 80% 100% 
proportion in % 
 
 
 
Figure 93 The proportion of the numbers of cities and size of the population to the total proportion in percent. The 
numbers between 1-7 horizontally refer to the decades in Table 27 (by the author) 
156 
 
 
 
Figure 94 Increasingly difference between the size and rank of the first city with the smallest city according to the results 
of the Rank-Size roll  (by the author) 
 
By the 1956s were 19 cities in this metropolitan area but today has 60 cities in 
Table 26. The percentage of numerical growth of the cities relative to the total of cities 
by today has decreased in 1966s surprisingly compared with the rate of the decade 
1956s that was 32% Table 27. The reason refers to the change of the political borders 
of this metropolitan area, separation of the major part of this region with urban and 
rural centers was added to the other provinces. Accordingly, the number of cities had 
decreased. As shown by the results of this research, before 1966s area of this region 
was about 14,758,918 hectares Figure 95, and today is about 2,261,555 hectares 
Figure 96.  As a result, the number of cities had been decreased. It can be seen in the 
map Figure 97 that a large area of the region separated from the main body of this 
region and added to the other region. For that reason, the biggest changes of rural 
areas to the new towns happened between the decades 1986-2006 11 and 16 Table 25. 
Over the seven decades of urbanization processes in this region, the numerical growth 
of the cities and towns was more than the population growth of urban zones. This fact 
has faced this study with challenging questions! Why are Irans' Urban Development 
Ministry and regional administrations investing many times to change rural areas to 
new towns more important than solving urban problems, polarization, and unequal 
distribution of resources and infrastructures among the cities? Why is it difficult for 
them to understand, changing villages to a town increases regional imbalances? 
157 
 
 
 
Figure 95  The geographical position and borders of the Mazandaran metropolitan area in the 1960s (by the author) 
 
Figure 96 The geographical position and borders of the Mazandaran metropolitan area in 2020 (by the author) 
 
Figure 97 The visual comparison of the changed borders from 1960 to 2020, By author 2020 (by the author) 
 
158 
 
 
8.9. The results of Location Quotient model (L.Q)  
The total share of Sari city in comparison with the total share at the national 
level 
Table 28 The total share of the three basic economic activities at the city and national levels in the 1966s (by the author) 
L.Q 
   
City National 
  
Agricultural 6649 3281125 
 
Industry 4913 1856548 
 
Servicing 8389 1833333 
 
SUM 19951 6971006 
 
 
Table 29 The rate of L.Q of Sari city at the national levels in the 1966s (by the author) 
City  National  LQ National 
33.326% 47.068% 0.708% 
24.625% 26.632% 0.924% 
42.048% 26.299% 1.598% 
100 100 
 
 
Table 30 The total share of the three basic economic activities at the city and national levels in the 1976s (by the author) 
L.Q  
   
City National 
  
Agricultural 8366 2991802 
 
Industry 7002 3009401 
 
Servicing 9257 2719020 
 
SUM 24625 8720223 
 
 
Table 31 The rate of L.Q of Sari city at the national levels in the 1976s (by the author) 
LQ 
City  National  
National 
33.973% 34.308% 0.990% 
28.434% 34.510% 0.823% 
37.591% 31.180% 1.205% 
100 100 
 
 
 
 
 
159 
 
 
The total share of the city in comparison with the total share at the national, 
region, and county levels 
Table 32 The total share of the three basic economic activities at the city, county, regional and national levels in the 
1986s (by the author) 
Region County City National 
 
Agricultural 217056 38280 988 3190761 
Industry 94929 6939 10341 2781008 
Servicing 205857 25643 20736 5029766 
5178 7086 3206 110015
SUM 
42 2 5 35 
 
Table 33 The percent of the activities of Sari city at the city, county, regional, and national levels in the 1986s (by the 
author) 
Regional County  City  National  
41.915% 54.020% 3.081% 29.002% 
18.331% 9.792% 32.250% 25.278% 
40 36.187% 64.668% 45.718% 
100 100 100 100 
 
 
Table 34 The rate of L.Q of Sari city at the county, regional, and national levels in the 1986s (by the author) 
LQ LQ LQ 
Regional County National 
0.0735% 0.057% 0.106% 
1.759% 3.293% 1.275% 
1.626% 1.787% 1.414% 
 
 
Table 35 The total share of the three basic economic activities at the city, county, regional and national levels in the 
1996s (by the author) 
L.Q 
 Reg ion Cou nty Ci ty Natio nal 
 Agricu ltural 202278 28932 13339 3357263 
 Industry 153809 12618 11927 4472958 
 Servicing 278537 27597 21746 6484323 
 SUM 634624 69147 47012 14314544 
  
 
160 
 
 
Table 36 The percent of the activities of Sari city at the county, regional, city, and national levels in the 1996s (by the 
author) 
Regional County City National 
31.873% 41.841% 28.373% 23.453% 
24.236% 18.248% 25.370% 31.247% 
43.890% 39.910% 46.256% 45.298% 
100 100 100 100 
 
 
Table 37 The rate of L.Q of Sari city at the county, regional, and national levels in the 1996s (by the author) 
LQ Regional LQ County LQ National 
0.890% 0.678% 1.209% 
1.046% 1.390% 0.811% 
1.053% 1.158% 1.021% 
 
Table 38 The total share of the three basic activities at the city, county, regional and national levels in the 2006s (by the 
author) 
L.Q 
     
Region County City National 
  
Agricultural 193565 32489 19283 3686747 
 
Industry 268071 18389 24740 6493398 
 
Servicing 443404 34094 45268 9808691 
 
SUM 905040 84972 89291 19988836 
 
 
Table 39 The percent of the activities of Sari city at the county, regional, and national levels in the 2006s (by the author) 
Region Percent County Percent City Percent National Percent 
21.387% 38.234% 21.595% 18.444% 
29.619% 21.641% 27.707% 32.485% 
48.992% 40.123% 50.697% 49.070% 
100 100 100 100 
 
Table 40 The rate of L.Q of Sari city at the county, regional, and national levels in the 2006s (by the author) 
LQ Regional LQ County LQ National 
1.009% 0.564% 1.170% 
0.935% 1.280% 0.852% 
1.034% 1.263% 1.033% 
 
 
161 
 
 
Table 41 The total share of the three basic activities at the city, county, regional and national levels in the 2016s (by the 
author) 
Regional County City National 
 
Agricultural 188826 42803 20346 4621315 
Industry 303638 22345 25421 7683721 
Servicing 464946 32854 47543 12074964 
SUM 957410 98002 93310 24380000 
 
Table 42 The percent of the activities of Sari city at the city, county, regional, and national levels in the 2016s (by the 
author) 
Regional Percent County Percent City Percent National Percent 
19.722% 43.675% 21.804% 18.955% 
31.714% 22.800% 27.243% 31.516% 
48.562% 33.523% 50.951% 49.528% 
100 100 100 100 
 
Table 43 The rate of L.Q of Sari city at the county, regional, and national levels in the 2016s (by the author) 
LQ 
LQ Regional LQ County 
National 
1.105% 0.499% 1.150% 
0.859% 1.194% 0.864% 
1.049% 1.519% 1.028% 
 
 
 
 
 
 
 
 
 
 
 
162 
 
 
The rate of L.Q of Sari city for all decades at the national level 
Table 44 The rate of L.Q of the activities of Sari city at the national level, 1966-2016 (by the author) 
Decades 1966 1976 1986 1996 2006 2016 
Agricultural 0.708% 0.990% 0.106% 1.209% 1.170% 1.150% 
Industry 0.924% 0.823% 1.275% 0.811% 0.852% 0.864% 
Servicing 1.598% 1.205% 1.414% 1.0211% 1.033% 1.028% 
 
 
Figure 98 The L.Q of the activities of Sari city at the national level, 1966-2016 (by the author) 
 
The final results for the agricultural sector show the development and independence 
of the sari city in the share of farm goods at the national level from 1966 to today. In 
1966 the rate of the L.Q model was lower than 1 (0.708<1), and it means that time the 
city was of importer of agricultural goods. In 1976, the rate of L.Q had considerably 
increased and was (0.990). On the one hand, the rate is lower than 1, but on the other 
hand, if the rate L.Q is equal with 1 (L.Q = 1), it means the city in the mentioned part 
is independent. Accordingly, it is not false if we argue that this city in 1976 would be 
independent rather than an importer of goods. Because, based on the results, the rate 
of L.Q in the following decades is more than 1, and the cities from this decade are 
independent and are the exporter of agricultural goods at the national levels. In 2006 
the city experienced the highest export rate, and in the next decade faced with a 0.2% 
163 
 
 
decrease. But this reduction is not limited to the mentioned sector also the industry 
and servicing activities faced with a declination.  
The other considerable change happened in the agricultural sector in 1986, and the 
value of the share of agricultural goods for this city had decreased dramatically. 
Because, in addition to the unwelcome revolution in 1979, one year later, Iran faced 
the war that was started by the country Iraq in the 1980s. So, basic economic sectors 
were under negative consequences of revolution and war at the national level, and as a 
result, the city experienced a decrease in production. But after the war, concerning the 
result as shown in Figure 98, the share of this city has increased rapidly and by today 
has the first place than other sectors. One of the main reasons referred to geographical 
location and particular climatic condition of this metropolitan area than the other 
regions in Iran. This region is the wettest region and always recorded the highest 
rainfall rate than the other regions in Iran. So, such perfect conditions have developed 
agricultural activities in this region, and most people are working in this sector. 
 
 
 
 
 
 
 
 
 
 
 
 
164 
 
 
The rate of L.Q of Sari city for all decades in the Mazandaran metropolitan 
area 
Table 45 The rate of L.Q of the activities of Sari city at the regional level, 1986-2016 (by the author) 
Decades  L.Q Sari 1986 L.Q Sari 1996 L.Q Sari 2006 L.Q Sari 2016 
Agricultural 0.073% 0.890% 1.009% 1.105% 
Industry 1.759% 1.046% 0.935% 0.859% 
Servicing 1.626% 1.053% 1.034% 1.049% 
 
 
Figure 99 The L.Q of the economic activities of Sari city at the regional level, 1986-2016 (by the author) 
 
Unfortunately, there is no statistical data around the above sectors before 1986 at 
the regional level. Concerning the model results, agricultural activities ranked above 
the other sectors on the graph and tables. And then servicing and industry parts placed 
in the second and third places. 
In the agricultural sector, the rates of share of the city at the regional level except 
the last decade are more than the national level. There are considerable differences 
between the values of agricultural and servicing activities with the industrial sector. 
For the service sector, there are no remarkable differences between the decades and 
rates of share. 
 
 
165 
 
 
The rate of L.Q of Sari city for all decades at the county level 
Table 46 The rate of L.Q of the activities of Sari city at the county level, 1986-2016 (by the author) 
Decades L.Q Sari 1986 L.Q Sari 1996 L.Q Sari 2006 L.Q Sari 2016 
Agricultural 0.05% 0.678% 0.564% 0.499% 
Industry 3.293% 1.390% 1.280% 1.194% 
Servicing 1.787% 1.158% 1.263% 1.519% 
 
 
Figure 100 The L.Q of the activities of Sari city at the regional level, 1986-2016 (by the author) 
 
According to the results of the L.Q model, the place of share of the city has 
changed surprisingly. The city at the county level has played its dominant role in 
servicing activities while agricultural servicing at the regional and national levels. As 
shown in Figure 100, in the servicing sector, after the 1996s, the graph has moved 
upward and shown a slight growth for the 2016s. And the towns and non-urban places 
around the city tend to meet their needs and receive services from the capital.  After 
that, the industry and agricultural sectors got the second and the third places.  
 
 
166 
 
 
8.10. The results of Isard's longitudinal and transverse 
model  
The proportion of the activities of Sari compared at the national level 1966-
1976 
Table 47 The proportion of the activities of Sari city compared at the national level between 1966-1976 (by the author) 
National City 
Agricu lture 91.18 125.82 
Industry 162.09 142.51 
Servicing 148.31 110.34 
Average Economic Growth 125.09 176.51 
 
 
Figure 101 The matrix of the activities of Sari city at the national level between 1966-1976 (by the author) 
 
167 
 
 
According to the results of the Isard model in Figure 101, the agricultural sector has 
been placed in part III of the matrix. The rate of this activity between 1966s-1976s for 
the city is 125.82%, near the average economic growth at the national level 125.09%, 
but 50.68% lower than the average economic growth rate of the city that was 
176.51%. 
But both industry and service sectors have been placed in part IV of the matrix. For 
the industry sector, the activity rate was 33.99%, actually lower than the average 
growth rate of the city but 17.42% more than the national level.  For the service 
sector, the rate of this activity was lower than the average economic growth; the rates 
of both sectors, respectively, are 66.16% and 14.74%.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
168 
 
 
The proportion of the activities of Sari city compared at the national level 
between 1976-1986 
Table 48 The proportion of the activities of Sari city compared at the national level between 1976-1986 (by the author) 
National City 
Agricu lture 106.65 119.38 
Industry 92.41 147.68 
Servicing 184.98 224.00 
Average Economic Growth 126.16 166.76 
 
 
Figure 102 The matrix of the activities of Sari city at the national level between 1976-1986 (by the author) 
 
During the decades 1976s-1986s, the situation and rank for basic economic 
activities have changed. With a 224% rate, the city's service sector has placed in part I 
of the matrix above the other sectors. It means the rate of this activity is about 57.24% 
more than the average economic growth of the city and about 97.84% more than 
national levels. In this phase, the spatial economic organization of the city has 
169 
 
 
changed, and the service sector became the highest primary economic activity. The 
city became a supplier of services to the other cities and non-urban areas at the 
regional and national levels.  
In the industry sector, the activity rate at the city level is about 19.07% lower than 
the average economic growth rate and lower than the average economic growth rate at 
the national level. As shown in Figure 102, the industry sector has been placed in part 
II of the matrix.  
Unfortunately, for the agricultural sector, the activity rate is lower than the average 
economic growth rate at both city and national levels. Also, this rate has reduced in 
comparison with the last decade.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
170 
 
 
The proportion of the activities of Sari city compared at the national level 
between 1986-1996 
Table 49 The proportion of the activities of Sari city compared at the national level 1986-1996 (by the author) 
National City 
Agricu lture 105.21 133.55 
Industry 160.83 115.33 
Servicing 128.91 104.87 
Average Economic Growth 130.11 114.48 
 
 
Figure 103 The matrix of the activities of Sari city at the national level between 1986-1996 (by the author) 
According to the results, the position of the three sectors has changed on the matrix 
dramatically. In this decade for this city except for agricultural industry that has 
experienced positive growth, rate of the other activities has been decreased 
significantly about -52.27% compared to the last decade.  
171 
 
 
The agricultural sector experienced sizeable growth, about 19.06% more than the 
average economic growth at the city and national levels. As illustrated on the matrix, 
this sector has moved from part III to part II. The activity rate has increased at the 
local level for the industry sector but was lower than the average economic growth 
rate at the national level. Compared to the last decade, this sector has moved from part 
II to part IV on the matrix but placed on the border. 
For the service sector, unfortunately, the rate of decrease is considerably much, 
about -119.12%. In this decade, the activity rates are remarkably lower than the 
average economic growth for both city and national levels. At the national, about -
56.06% rate of this servicing activities had decreased, and in comparison with last 
decade, its position has changed from part I to part III on the matrix. 
 
 
 
 
 
 
 
 
 
 
 
 
 
172 
 
 
The proportion of the activities of Sari city compared at the national level 
between 1996-2006 
Table 50 The proportion of the activities of Sari city compared at the national level 1996-2006 (by the author) 
National City 
Agricu lture 109.81 144.56 
Industry 145.17 207.42 
Servicing 151.26 208.16 
Average Economic Growth 139.64 189.93 
 
 
Figure 104 The matrix of the activities of Sari city at the national level between 1996-2006 (by the author) 
 
Concerning the results of this decade, both city and national levels have 
experienced positive average economic growth, respectively 189.93% and 139.64%. 
Also, industry and service sectors have been faced with substantial growth and, in 
comparison with the last decade, displaced their positions from parts III and IV to part 
173 
 
 
I, as shown in the above matrix. It means the industry and service sector activities 
have grown up more than average economic growth at both city and national levels.  
For the agricultural sector, the activity rate was lower than the average economic 
growth at the city level and more than the national level and located in part III of the 
matrix. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
174 
 
 
The proportion of the activities of Sari city compared at the national level 
between 2006-2016 
Table 51 The proportion of the activities of Sari city compared at the national level 2006-2016 (by the author) 
2006-2016 National City 
Agriculture 125.34 105.51 
Industry 118.33 102.75 
Servicing 123.10 105.02 
Average Economic Growth 121.96 104.50 
 
 
 
Figure 105 The matrix of the activities of Sari city at the national level between 2006-2016 (by the author) 
 
In this decade, all three basic economic sectors at the city level have been faced 
with a dramatic decrease rate of activities and the national sectors except the 
175 
 
 
agricultural activities. It means the country has experienced a downturn, and the 
average economic growth rate has considerably decreased Table 51.  
As illustrated in the above matrix, the industry sector has been placed in part III., so 
it means the activities rates at both levels are lower than the rate of average economic 
growth. Servicing and agricultural parts are located in part I but closed to the line. It 
means the growth rate is hopeful and better than other parts in terms of activity. The 
activity rate for the agricultural sector at the local level is1.01, and for the service 
sector is about 0.52 %. Also, at the national level, respectively, 3.39% and 1.14% 
were more than the average economic rates.  
 
176 
 
 
8.11. The results of Lorenz Curve and calculating Gini Coefficient 
The results of Lorenz Curve for the decade 1986 
The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank for the 1986s 
Table 52 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 1986s (by the author) 
The cumulative 
The The population of the The simple The simple distribution The cumulative The simple distribution The density of 
Groups Ranks Cities  Number of cities The ranks of density The simple population percent of the 
population  classes rank  of cities in % percent of cities  of the population in % population  
population in % 
1 Sari 141020 0.03030303 1 0.157096117 1 
2 Amol 118242 0.03030303 0.96969697 0.131721451 0.842903883 
100000-250000 4 483870 12.12% 95.45% 53.90% 78.42% 
3 Babol 115320 0.03030303 0.939393939 0.128466347 0.711182432 
4 Ghaemshahr 109288 0.03030303 0.909090909 0.121746706 0.582716085 
50000-99999 5 Behshahr 52461 1 52461 0.03030303 3.03% 0.878787879 87.88% 0.058441493 5.84% 0.46096938 46.10% 
6 Tonekabon 29380 0.03030303 0.848484848 0.032729286 0.402527886 
7 Challos 29308 0.03030303 0.818181818 0.032649078 0.3697986 
25000-49999 8 Babolsar 28589 5 140845 0.03030303 15.15% 0.787878788 78.79% 0.031848113 15.69% 0.337149522 33.77% 
9 Nooshahr 28216 0.03030303 0.757575758 0.031432591 0.305301409 
10 Ramsar 25352 0.03030303 0.727272727 0.028242099 0.273868818 
11 Neka 23604 0.03030303 0.696969697 0.026294829 0.245626719 
12 Freydonkenar 20997 0.03030303 0.666666667 0.023390634 0.21933189 
13 Juybar 18942 0.03030303 0.636363636 0.021101366 0.195941257 
14 Amirkolah 18295 0.03030303 0.606060606 0.020380609 0.174839891 
10000-24999 15 Galogah 18073 8 138331 0.03030303 24.24% 0.575757576 59.09% 0.020133301 15.41% 0.154459282 16.86% 
Katalem 
16 13509 0.03030303 0.545454545 0.01504901 0.134325981 
Sadatshahr 
17 Nor 13055 0.03030303 0.515151515 0.014543255 0.11927697 
18 Mahmoodabad 11856 0.03030303 0.484848485 0.01320757 0.104733715 
19 Zirab 9595 0.03030303 0.454545455 0.010688819 0.091526145 
20 Rostamkolah 9220 0.03030303 0.424242424 0.010271069 0.080837326 
21 Abbasabad 8169 0.03030303 0.393939394 0.009100257 0.070566257 
5000-9999 22 Khoramabad 8154 7 56100 0.03030303 21.21% 0.363636364 36.36% 0.009083547 6.25% 0.061466 6.24% 
23 Shirgah 7452 0.03030303 0.333333333 0.008301519 0.052382454 
24 Salmanshahr 7087 0.03030303 0.303030303 0.00789491 0.044080934 
25 Polsefeed 6423 0.03030303 0.272727273 0.007155215 0.036186024 
26 Nashtarood 4760 0.03030303 0.242424242 0.005302634 0.02903081 
27 Kelarabad 4267 0.03030303 0.212121212 0.004753433 0.023728175 
28 Royan 4035 0.03030303 0.181818182 0.004494985 0.018974742 
29 Kelardasht 4030 0.03030303 0.151515152 0.004489415 0.014479757 
Under 5000 8 26060 24.24% 13.64% 2.90% 1.32% 
30 Marzanabad 3889 0.03030303 0.121212121 0.004332342 0.009990342 
31 Keeyakolah 2964 0.03030303 0.090909091 0.003301893 0.005658 
32 Rineh-e-Larijan 1225 0.03030303 0.060606061 0.001364649 0.002356108 
33 Alasht 890 0.03030303 0.03030303 0.000991459 0.000991459 
SUM 897667 33 897667 100.00% 100.00% 
        
177 
 
 
The final curve considering the results of Lorenz model (Table 52) and calculating 
Gini Coefficient for the decade 1986. 
 
 
Figure 106 the results of the Lorenz Curve and Gini Coefficient for the decade 1986 (by the author) 
 
Concerning the results of the Lorenz model, this Metropol had 33 cities with 
897667 populations in 1986s. According to the showed results in Table 52, the listed 
cities have been placed in the six subgroups and ranked according to the size of the 
population. The results represent centralization in the urban system, an unbalance in 
the urban hierarchies, the polarization of population, and urban growth, particularly in 
the big and medium-sized cities. Surprisingly, more than 53.90% of the population 
has concentrated just in the four medium-sized cities (big-class). And in the second 
group, just one city placed with 5.84% of the population of the Metropol, and the rest 
are small urban areas. It means about 59.75% of the population, about 536331 people, 
have been concentrated in the first five cities, and 40,25% of the population, about 
361336 people, lived in 28 towns. While, simple distribution of the medium-sized 
cities for the first group is 12,12% and the second group is 3,03, but they have 
178 
 
 
124,52% of the cumulative population. For the other groups, the simple distribution 
of the small urban area is 84.85%, but the cumulative percent of the population is 
about 58,19.  
According to the illustrated results on the Lorenz curve Figure 106, the distance 
between the Lorenz curve and the normal line is considerable. And distribution of 
cities in the small-sized cities is more than bigger groups of cities. Especially for the 
ranges between 80-100, the space between points is more and not normal. These 
ranges refer to both medium-classed size cities (small and big).  
Based on the Gini coefficient, if G=0 means complete equality, G>0 and up to 
0.25, means relative unequal. If the result is between 0 .25 – 0.5 expresses Unequal; if 
between 0.5 – 0.75 means more unequal, and if between 0.75 – 100 says total 
inequality (Critical situation). As is shown in Figure 106, the Gini coefficient for this 
decade is 0.59, so it means an unequal distribution of population concerning the size 
of the cities. 
179 
 
 
The results of Lorenz Curve for the decade 1996: 
The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 1996s 
Table 53 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 1996s (by the author) 
The simple The simple The cumulative 
New The The population of The cumulative The simple 
Groups Ranks Cities  Number of cities The simple rank  distribution of The ranks of density distribution of the The density of population  percent of the 
cities population  the classes percent of cities  population 
cities in % population in % population in % 
1  Sari 195882 0.027027027 1 0.160122486 1 
2  Amol 159092 0.027027027 0.972972973 0.130048736 0.839877514 
100000-250000 4 656606 10.81% 95.95% 53.67% 78.25% 
3  Babol 158346 0.027027027 0.945945946 0.129438923 0.709828778 
4  Ghaemshahr 143286 0.027027027 0.918918919 0.117128223 0.580389855 
50000-99999 5  Behshahr 72067 1 72067 0.027027027 2.70% 0.891891892 89.19% 0.058910707 5.89% 0.463261633 46.33% 
6  Challos 41403 0.027027027 0.864864865 0.033844617 0.404350925 
7  Babolsar 38644 0.027027027 0.837837838 0.03158929 0.370506308 
8  Neka 35208 0.027027027 0.810810811 0.028780554 0.338917018 
25000-49999 9  Nooshahr 35133 7 240968 0.027027027 18.92% 0.783783784 78.38% 0.028719246 19.70% 0.310136464 31.28% 
10  Tonekabon 33650 0.027027027 0.756756757 0.027506977 0.281417218 
11  Ramsar 28954 0.027027027 0.72972973 0.023668262 0.253910241 
12  Freydonkenar 27976 0.027027027 0.702702703 0.022868802 0.23024198 
13  Juybar 23909 0.027027027 0.675675676 0.019544259 0.207373178 
14  Amirkolah 21280 0.027027027 0.648648649 0.0173952 0.187828919 
15  Mahmoodabad 20054 0.027027027 0.621621622 0.016393014 0.170433719 
16  Galogah 18073 0.027027027 0.594594595 0.014773658 0.154040705 
10000-24999 17  Zirab 17196 9 154814 0.027027027 24.32% 0.567567568 56.76% 0.01405676 12.66% 0.139267047 14.26% 
18  Nor 16808 0.027027027 0.540540541 0.013739592 0.125210287 
19  Katalem Sadatshahr 16239 0.027027027 0.513513514 0.013274466 0.111470695 
20  Rostamkolah 10773 0.027027027 0.486486486 0.00880632 0.098196229 
21  Kelardasht 10482 0.027027027 0.459459459 0.008568444 0.089389909 
22  Khoramabad 9881 0.027027027 0.432432432 0.00807716 0.080821465 
23  Shirgah 9546 0.027027027 0.405405405 0.007803317 0.072744305 
24  Abbasabad 9384 0.027027027 0.378378378 0.007670891 0.064940989 
25  Salmanshahr 8302 0.027027027 0.351351351 0.006786417 0.057270098 
26 + Sorrak 8236 0.027027027 0.324324324 0.006732465 0.050483681 
5000-9999 10 79813 27.03% 31.08% 6.52% 4.84% 
27 + Chamestan 7926 0.027027027 0.297297297 0.006479058 0.043751216 
28  Polsefeed 7648 0.027027027 0.27027027 0.006251809 0.037272158 
29  Keeyakolah 6810 0.027027027 0.243243243 0.005566791 0.031020349 
30  Marzanabad 6488 0.027027027 0.216216216 0.005303574 0.025453559 
31  Royan 5592 0.027027027 0.189189189 0.004571145 0.020149985 
32  Kelarabad 4973 0.027027027 0.162162162 0.004065147 0.01557884 
33  Nashtarood 4770 0.027027027 0.135135135 0.003899206 0.011513693 
34 + Kiyahsar 3782 0.027027027 0.108108108 0.003091572 0.007614487 
Under 5000 6 19058 16.22% 9.46% 1.56% 0.68% 
35 + Sorhkrood 3772 0.027027027 0.081081081 0.003083397 0.004522915 
36  Rineh-e-Larijan 1337 0.027027027 0.054054054 0.001092922 0.001439518 
37  Alasht 424 0.027027027 0.027027027 0.000346596 0.000346596 
 SUM 1223326 1223326 1 100.00% 1 100.00% 
       
 
180 
 
 
The final curve considering the results of Lorenz model (Table 53) and calculating 
Gini Coefficient for the decade 1996. 
 
 
Figure 107 the results of the Lorenz Curve and Gini Coefficient for the decade 1996 (by the author) 
 
Concerning the final results of the Lorenz model, the numbers of the cities were 37 
with 1223326 dwellers in 1996s. There are no considerable changes in comparison 
with the last decade. According to Table 53, the results represented a continuation of 
imbalance and centralization in the urban hierarchies, which were started in the past. 
More than 53.67% of the population, like before, is concentrated just in the four 
medium-sized cities (big-class). And just one city has placed in the second group with 
5.89% of the total urban population of the region, and the rest are small urban areas. It 
means 59.56% of the population, about 728673 people, have been concentrated in the 
five cities, and 40,44% of the population, about 494653 people, have been placed in 
the 32 small cities. The simple distribution of the medium-sized cities for the first 
group is 10.81%, and the second group is 2.70, but they have 124,58% of the 
cumulative population. For the other groups, the simple distribution of the small 
urban area is 86.49%, but the cuamulative percent of the population is 51,06. As a 
181 
 
 
result, the is drastic contrast between the size of population accumulation and the 
growth of the cities in this region.    
Concerning the illustrated results on the Lorenz curve Figure 107, the distance 
between the Lorenz curve and the normal line is like before did not happen positive 
changes in the share of the population between the cities and towns. As shown in 
Figure 107, the Gini coefficient for this decade is 0.59, and it means an unequal 
distribution of population concerning the size of cities.  
 
 
182 
 
 
The results of Lorenz Curve for the decade 2006:  
The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 2006s 
Table 54 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 2006s (by the author) 
New The The population of the The simple The simple distribution The ranks of The cumulative percent The simple distribution The density of The cumulative percent 
Groups Rank Cities  Number of cities The simple population 
cities population  classes rank  of cities in % density of cities  of the population in % population  of the population in % 
1  Sari 261293 0.019607843 1 0.168126743 1 
2  Babol 201335 0.019607843 0.980392157 0.129547281 0.831873257 
100000-250000 4 837094 7.84% 97.06% 53.86% 77.70% 
3  Amol 199698 0.019607843 0.960784314 0.128493967 0.702325976 
4  Ghaemshahr 174768 0.019607843 0.941176471 0.112452972 0.573832009 
5  Behshahr 84117 0.019607843 0.921568627 0.054124363 0.461379037 
50000-99999 2 134149 3.92% 91.18% 8.63% 43.43% 
6  Babolsar 50032 0.019607843 0.901960784 0.032192662 0.407254673 
7  Neka 46291 0.019607843 0.882352941 0.029785547 0.375062012 
8  Challos 45625 0.019607843 0.862745098 0.029357015 0.345276464 
9  Tonekabon 43842 0.019607843 0.843137255 0.028209759 0.315919449 
10  Nooshahr 42175 0.019607843 0.823529412 0.027137142 0.28770969 
25000-49999 11  Freydonkenar 34496 9 324764 0.019607843 17.65% 0.803921569 80.39% 0.022196156 20.90% 0.260572547 26.92% 
12  Ramsar 32085 0.019607843 0.784313725 0.020644818 0.238376391 
13  Mahmoodabad 27748 0.019607843 0.764705882 0.017854213 0.217731573 
14  Juybar 27211 0.019607843 0.745098039 0.017508685 0.19987736 
15  Amirkolah 25291 0.019607843 0.725490196 0.016273277 0.182368675 
16  Nor 22491 0.019607843 0.705882353 0.014471641 0.166095398 
17  Galogah 18727 0.019607843 0.68627451 0.012049728 0.151623757 
18  Zirab 18388 0.019607843 0.666666667 0.011831601 0.139574029 
 Katalem 
19 17955 0.019607843 0.647058824 0.011552991 0.127742428 
10000-24999 Sadatshahr 8 122372 15.69% 63.73% 7.87% 12.56% 
20  Kelardasht 11999 0.019607843 0.62745098 0.007720654 0.116189437 
21  Rostamkolah 11408 0.019607843 0.607843137 0.00734038 0.108468783 
22  Abbasabad 11278 0.019607843 0.588235294 0.007256732 0.101128403 
23 + Khalilshar 10126 0.019607843 0.568627451 0.006515488 0.093871671 
24  Khoramabad 9945 0.019607843 0.549019608 0.006399025 0.087356183 
25  Salmanshahr 9664 0.019607843 0.529411765 0.006218218 0.080957158 
26  Chamestan 9499 0.019607843 0.509803922 0.00611205 0.07473894 
27  Sorrak 8822 0.019607843 0.490196078 0.00567644 0.06862689 
28  Polsefeed 8708 0.019607843 0.470588235 0.005603088 0.062950449 
29  Shirgah 8611 0.019607843 0.450980392 0.005540674 0.057347361 
30  Keeyakolah 7472 0.019607843 0.431372549 0.004807794 0.051806687 
5000-9999 31  Marzanabad 7102 15 114910 0.019607843 29.41% 0.411764706 41.18% 0.004569721 7.39% 0.046998893 4.91% 
32 + Gatab 6956 0.019607843 0.392156863 0.004475779 0.042429172 
33 + Izadshahr 6888 0.019607843 0.37254902 0.004432025 0.037953393 
34 + Bahnamir 6848 0.019607843 0.352941176 0.004406287 0.033521368 
35  Sorhkrood 6620 0.019607843 0.333333333 0.004259582 0.029115081 
36  Royan 6351 0.019607843 0.31372549 0.004086497 0.024855499 
37  Nashtarood 5967 0.019607843 0.294117647 0.003839415 0.020769003 
38  Kelarabad 5457 0.019607843 0.274509804 0.00351126 0.016929588 
39  Kiyahsar 3672 0.019607843 0.254901961 0.002362717 0.013418328 
40 + Kalehbast 3561 0.019607843 0.235294118 0.002291295 0.011055611 
41 + Khoshrodpey 3022 0.019607843 0.215686275 0.00194448 0.008764316 
42 + Galogahe Babol 2519 0.019607843 0.196078431 0.001620829 0.006819836 
43 + Kohekheyl 1950 0.019607843 0.176470588 0.001254711 0.005199007 
44  Baladeh 1340 0.019607843 0.156862745 0.000862212 0.003944296 
Under 5000 45  Rineh-e-Larijan 1213 13 20854 0.019607843 25.49% 0.137254902 13.73% 0.000780494 1.34% 0.003082084 0.45% 
46 + Dabodasht 1096 0.019607843 0.117647059 0.000705212 0.00230159 
47  Alasht 984 0.019607843 0.098039216 0.000633146 0.001596378 
48 + Marzikolah 525 0.019607843 0.078431373 0.000337807 0.000963232 
49 + Zargarmahaleh 425 0.019607843 0.058823529 0.000273463 0.000625425 
50 + Gazanak 362 0.019607843 0.039215686 0.000232926 0.000351962 
51 + Farim 185 0.019607843 0.019607843 0.000119037 0.000119037 
 SUM 1554143 1554143 100.00% 387.25% 100.00% 165.97% 
       
 
183 
 
 
The final curve considering the results of Lorenz model (Table 54) and calculating 
Gini Coefficient for the decade 2006. 
 
 
Figure 108 the results of the Lorenz Curve and Gini Coefficient for the decade 2006 (by the author) 
 
With respect to the results of the Lorenz model, the number of cities has 
substantially has grown up to 51 cities with 1554143 dwellers in 2006s. According to 
Table 54, the results represented drastic changes in the rank and number of cities but 
not the population size. How is it possible such emerge of many new towns during a 
decade! The number of small cities has been increased surprisingly, especially in the 
groups under 10000 dwellers. In this decade, for the first time, we are witnessing 
emerge of the Sari as the first city that has been placed in class C1 of the urban 
hierarchies of this metropolitan area Table 54. This numerical increase of cities, 
neglecting providing needed infrastructures to meet people's basic needs such as jobs, 
homes, entertainment, and recreation, has increased the imbalance and centralization 
in the urban hierarchies. According to the results, on the one hand, we are witnessing 
a numerical increase of new small cities, but on the other hand, seeing physical 
growth and agglomeration of the population in the big cities. It should be clear for the 
administrations, and they have to learn; changing villages to small cities is contrary to 
184 
 
 
the migration controlling policies.  More than 53.86% of the population is 
concentrated just in the four cities of the big-class (medium-sized). And then in the 
second group, medium-sized (small-class) for the first time two cities have been 
placed in this group and encompassed 8.63% of the total urban population. 
Accordingly, 70.70 % of the cumulative population, 837094 people, have been 
concentrated in the first four cities, and 43.43% of the population, 134149 people, in 
the second group, and 44.84% of the people in the 45 small cities. Concerning the 
illustrated results on the Lorenz curve Figure 108, the distance between the Lorenz 
curve and the normal line has increased more than the last decades and represented 
the highest rate of inequality. As shown in Figure 108, the Gini coefficient for this 
decade is 0.73 and expresses the continuation of unequal distribution of population 
regarding the size of cities.  
185 
 
 
The results of Lorenz Curve for the decade 2016: 
The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 2016s 
Table 55 The spatial distribution of cities in the Mazandaran metropolitan area considering the factors population and rank in the 2016s (by the author) 
The simple The simple The cumulative 
New The The population of The simple The ranks of The cumulative The simple The density of 
Groups Rank Cities  Number of cities distribution of cities distribution of the percent of the 
cities population  the classes rank  density percent of cities  population population  
in % population in % population in % 
1  Sari 347402 0.016666667 0.966666667 0.178761929 0.996544162 
250000-499999 2 597619 
2  Babol 250217 0.016666667 0.95 0.128753644 0.817782233 
6.67% 94.17% 53.52% 76.75% 
3  Amol  237528 0.016666667 0.933333333 0.122224292 0.689028588 
100000-249999 2 442481 
4  Ghaemshahr 204953 0.016666667 0.916666667 0.105462242 0.566804296 
5  Behshahr 94702 0.016666667 0.9 0.048730612 0.461342055 
6  Challos 65196 0.016666667 0.883333333 0.033547771 0.412611443 
50000-99999 7  Neka 60991 5 336289 0.016666667 8.33% 0.866666667 87.33% 0.031384013 17.30% 0.379063672 38.35% 
8  Babolsar 59966 0.016666667 0.866666667 0.030856581 0.347679659 
9  Tonekabon 55434 0.016666667 0.85 0.028524559 0.316823078 
10  Nooshahr 49403 0.016666667 0.833333333 0.0254212 0.288298519 
11  Freydonkenar 38154 0.016666667 0.816666667 0.019632825 0.26287732 
12  Ramsar 35997 0.016666667 0.8 0.018522902 0.243244495 
25000-49999 13  Juybar 32924 7 245747 0.016666667 11.67% 0.783333333 78.81% 0.016941635 12.65% 0.224721593 22.77% 
14  Mahmoodabad 31844 0.016666667 0.766666667 0.016385901 0.207779958 
15  Amirkolah 30478 0.016666667 0.766666667 0.015683001 0.191394057 
16  Nor 26947 0.016666667 0.75 0.013866062 0.175711056 
17  Galogah 21352 0.016666667 0.733333333 0.010987054 0.161844994 
18  Katalem Sadatshahr 20716 0.016666667 0.716666667 0.010659789 0.150857939 
19  Zirab 16191 0.016666667 0.7 0.008331369 0.14019815 
20  Abbasabad 13482 0.016666667 0.683333333 0.006937405 0.13186678 
21  Kelardasht 13401 0.016666667 0.666666667 0.006895725 0.124929376 
22  Rostamkolah 11686 0.016666667 0.65 0.006013241 0.118033651 
10000-24999 12 162698 20.00% 64.17% 8.37% 11.77% 
23  Khoramabad 11542 0.016666667 0.633333333 0.005939143 0.11202041 
24  Shirood 11377 0.016666667 0.616666667 0.005854239 0.106081267 
25  Chamestan 11194 0.016666667 0.6 0.005760073 0.100227027 
26  Khalilshar 11032 0.016666667 0.583333333 0.005676713 0.094466954 
27  Hachirood 10398 0.016666667 0.566666667 0.005350477 0.08879024 
28  Arateh 10327 0.016666667 0.55 0.005313943 0.083439763 
29  Salmanshahr 9656 0.016666667 0.533333333 0.004968668 0.07812582 
30  Sorrak 9208 0.016666667 0.516666667 0.004738142 0.073157152 
31  Shirgah 8671 0.016666667 0.5 0.004461819 0.068419011 
32  Polsefeed 8294 0.016666667 0.483333333 0.004267826 0.063957192 
33  Keeyakolah 8040 0.016666667 0.466666667 0.004137126 0.059689366 
34  Bahnamir 7906 0.016666667 0.45 0.004068174 0.055552239 
5000-9999 35 + Hadishahr 7889 17 126684 0.016666667 28.33% 0.433333333 40.00% 0.004059426 6.52% 0.051484065 4.47% 
36  Royan 7731 0.016666667 0.416666667 0.003978125 0.047424639 
37  Izadshahr 7439 0.016666667 0.4 0.003827871 0.043446514 
38  Gatab 7374 0.016666667 0.383333333 0.003794424 0.039618643 
39  Galogahe Babol 6908 0.016666667 0.366666667 0.003554635 0.035824219 
40  Sorhkrood 6699 0.016666667 0.35 0.003447091 0.032269584 
41  Marzanabad 6698 0.016666667 0.333333333 0.003446576 0.028822494 
186 
 
 
42  Nashtarood 6394 0.016666667 0.316666667 0.003290147 0.025375918 
43 + Kelarabad 6267 0.016666667 0.3 0.003224797 0.02208577 
44 + Emamzadehabdollah 5768 0.016666667 0.283333333 0.002968028 0.018860973 
45  Khoshrodpey 5742 0.016666667 0.266666667 0.002954649 0.015892945 
46 + Ejbarkollah 4499 0.016666667 0.25 0.002315041 0.015253337 
47 + Zargarmahaleh 3991 0.016666667 0.233333333 0.002053641 0.012938296 
48  Kiyahsar 3384 0.016666667 0.216666667 0.001741298 0.010884655 
49 + Pool 3150 0.016666667 0.2 0.001620889 0.009143358 
50  Kelarabad 3120 0.016666667 0.183333333 0.001605452 0.007522469 
51 + Marzikolah 2710 0.016666667 0.166666667 0.001394479 0.005917017 
52  Kohekheyl 2242 0.016666667 0.15 0.001153661 0.004522538 
Under 5000 53 + Farahabad 2217 13 31860 0.016666667 25.00% 0.133333333 15.38% 0.001140797 1.64% 0.004509673 0.62% 
54  Dabodasht 1758 0.016666667 0.116666667 0.00090461 0.003368876 
55  Alasht 1193 0.016666667 0.1 0.00061388 0.002464266 
56  Rineh-e-Larijan 982 0.016666667 0.083333333 0.000505306 0.001850386 
57  Baladeh 970 0.016666667 0.066666667 0.000499131 0.001345081 
58  PaeenHolar 956 0.016666667 0.05 0.000491927 0.00084595 
59  Farim 369 0.016666667 0.033333333 0.000189876 0.000354023 
60  Gazanak 319 0.016666667 0.016666667 0.000164147 0.000164147 
 SUM 1943378 1943378 100.00% 379.86% 100.00% 154.74% 
       
 
 
187 
 
 
The final curve considering the results of Lorenz model (Table 55) and calculating 
Gini Coefficient for the decade 2016. 
 
 
Figure 109 the results of the Lorenz Curve and Gini Coefficient for the decade 2016 (by the author) 
 
Concerning the results of the Lorenz model, the number of the cities substantially 
has grown up to 60 cities with about 1943378 dwellers in 2016. According to Table 
55, the results represent substantial changes in the rank and number of cities, 
especially in the first, second, third, and seventh groups of the big and small cities. 
Growth of big cities more than ever has been increased and continued agglomeration 
of cities.  In this decade, for the first time, two big cities (medium-class) have 
emerged. The number of cities in the third group has surprisingly increased, and now 
there are five cities in the medium-sized. Consequently, have been eight new small 
cities emerged in the last groups. Today there are 60 cities and small towns in this 
region, and the first city has 347402 dwellers; meanwhile, the last town has 319 
dwellers, which means the population size of the first city is 1089 times bigger than 
the last town.  
188 
 
 
According to the illustrated results in Figure 109, the distance between the normal 
line (line of equality) and the Lorenz Curve is more than ever happened. And the Gini 
coefficient is > 0.75, as shown on the graph 0.75228, so it means the balance and 
equality between the size of cities and distribution of population in this region are in 
the worst condition., and it's going to be more dramatic than before. These 
problematic conditions are consequences of uncontrolled urbanization, which was 
started in the last decades. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
189 
 
 
8.12. The results of Entropy Index 
The results of Entropy Index for the decade 1986: 
The rate of entropy of the spatial distribution of population and size of cities in 
the Mazandaran metropolitan area considering the actual population for the 
decade 1986. 
 
Table 56 The rate of entropy of the spatial distribution of population and size of cities according to the actual population 
for the decade 1986s (by the author) 
The real 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population  
100000-250000 483870 0.53903 -0.618 -0.3331 
50000-99999 52461 0.05844 -2.8397 -0.166 K=6 
25000-49999 140845 0.1569 -1.8521 -0.2906 Ln (k6)= 
10000-24999 138331 0.1541 -1.8701 -0.2882 1.7917595 
5000-9999 56100 0.0625 -2.7727 -0.1733 H=1.353894 
Under 5000 26060 0.02903 -3.5394 -0.1028 G=0.755623 
SUM 897667 1 1.3539 
 
 
The rate of entropy of the spatial distribution of population and size of cities in the 
Mazandaran metropolitan area considering the caculated optimal size of population by 
Zipf's law (Table 20) for the decade 1986. 
 
Table 57 The rate of entropy of the spatial distribution of population and size of cities according to the population of 
Zipf's law for the decade 1986  (by the author) 
The real 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population 
100000-250000 141020 0.24985 -1.3869 -0.3465 K=6 
50000-99999 70510 0.12493 -2.08 -0.2599 Ln (k6)= 
25000-49999 110466 0.19572 -1.6311 -0.3192 1.7917595 
10000-24999 136540 0.24191 -1.4192 -0.3433 H=1.687979 
5000-9999 79591 0.14102 -1.9589 -0.2762 G=0.942079 
Under 5000 26287 0.04657 -3.0667 -0.1428 
SUM 564413.2355 1 1.688 
 
 
190 
 
 
The results of Entropy Index for the decade 1996: 
The rate of entropy of the spatial distribution of population and size of cities in 
the Mazandaran metropolitan area considering the actual population for the 
decade 1996. 
Table 58 The rate of entropy of the spatial distribution of population and size of cities according to the actual population 
for the decade 1996s (by the author) 
The real 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population  
100000-250000 656606 0.5367384 -0.622245 -0.333982505 
50000-99999 72067 0.0589107 -2.831732 -0.16681936 k=6 
25000-49999 240968 0.1969777 -1.624665 -0.320022756 Ln (k6)= 
10000-24999 154814 0.1265517 -2.067104 -0.261595584 1.791759469 
5000-9999 79813 0.0652426 -2.729642 -0.178089027 H=1.325345898 
Under 5000 19058 0.0155788 -4.161842 -0.064836666 G=0.73968963 
SUM 1223326 1 -14.03723 1.3253 
 
The rate of entropy of the spatial distribution of population and size of cities in the 
Mazandaran metropolitan area considering the caculated optimal size of population by 
Zipf's law (Table 22) for the decade 1996. 
 
Table 59 The rate of entropy of the spatial distribution of population and size of cities according to the population of 
Zipf's law for the decade 1996 (by the author) 
The 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population  
100000-250000 195882 0.2380054 -1.435462 -0.34164768 
k=5 
50000-99999 163235 0.1983378 -1.617784 -0.32086766 
Ln (k5)= 
25000-49999 148777 0.1807708 -1.710526 -0.309213004 
1.609437912 
10000-24999 187044 0.2272672 -1.481629 -0.336725632 
H=1.597958939 
5000-9999 128077 0.155619 -1.860345 -0.289504963 
G=0.992867713 
SUM 823015.1127 1.5979 
  
 
 
 
191 
 
 
The results of Entropy Index for the decade 2006: 
The rate of entropy of the spatial distribution of population and size of cities in 
the Mazandaran metropolitan area considering the actual population for the 
decade 2006. 
Table 60 The rate of entropy of the spatial distribution of population and size of cities according to the actual population 
for the decade 2006s (by the author) 
The real 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population 
250000-500000 261293 0.168126743 -1.783037164 -0.29977623 
k=7 
100000-249999 575801 0.370494221 -0.992917432 -0.367870171 Ln (k7)= 
50000-99999 134149 0.086317025 -2.449728425 -0.211453269 1.945910149 
25000-49999 324764 0.208966614 -1.565580783 -0.327154115 H=1.656800065 
G=0.851426807 
10000-24999 122372 0.078739215 -2.541613962 -0.200124688 
5000-9999 114910 0.073937855 -2.604530334 -0.192573387 
Under 5000 20854 0.013418328 -4.311133771 -0.057848206 
SUM 1554143 1 1.6568 
  
 
The rate of entropy of the spatial distribution of population and size of cities in the 
Mazandaran metropolitan area considering the caculated optimal size of population by 
Zipf's law (Table 23) for the decade 2006. 
 
Table 61 The rate of entropy of the spatial distribution of population and size of cities according to the population of 
Zipf's law for the decade 2006 (by the author) 
The 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population 
250000-500000 261293 0.221297091 -1.508249175 -0.333771156 
k=6 
100000-249999 130647 0.110648546 -2.201396355 -0.243581305 Ln (k6)= 
50000-99999 204680 0.173349388 -1.752446135 -0.303785466 1.791759469 
H=1.765772001 
25000-49999 168700 0.14287713 -1.945770248 -0.278006069 G=0.985496118 
10000-24999 241814 0.204799717 -1.585722768 -0.324755574 
5000-9999 173601 0.147028341 -1.917129912 -0.281872431 
SUM 1180734 1 1.7657 
  
 
 
 
192 
 
 
The results of Entropy Index for the decade 2016: 
The rate of entropy of the spatial distribution of population and size of cities in 
the Mazandaran metropolitan area considering the actual population for the 
decade 2016. 
 
Table 62 The rate of entropy of the spatial distribution of population and size of cities according to the actual population 
for the decade 2016s (by the author) 
The real 
Groups Pi Ln(Pi) Pi*Ln(Pi) 
population 
250000-500000 597619 0.308581983 -1.175767724 -0.362820736 
100000-249999 442481 0.22847611 -1.476323626 -0.337304679 
k=7 
50000-99999 336289 0.17364362 -1.750750242 -0.304006609 Ln (k7)= 
25000-49999 245747 0.126892044 -2.0644186 -0.261958296 1.945910149 
H=1.708951863 
10000-24999 162698 0.084009497 -2.47682543 -0.208076858 G=0.87822753 
5000-9999 126684 0.065413583 -2.727025355 -0.178384499 
Under 5000 25144 0.012983164 -4.344101852 -0.056400186 
SUM 1936662 1 -16.01521283 1.7089 
 
 
The rate of entropy of the spatial distribution of population and size of cities in the 
Mazandaran metropolitan area considering the caculated optimal size of population by 
Zipf's law (Table 24) for the decade 2016. 
 
Table 63 The rate of entropy of the spatial distribution of population and size of cities according to the population of 
Zipf's law for the decade 2016 (by the author) 
The 
Group Pi Ln(Pi) Pi*Ln(Pi) 
population 
250000-500000 347402 0.21522714 -1.536061346 -0.33060209 
100000-249999 289502 0.17935595 -1.718382902 -0.308202197 k=6 
Ln (k6)= 
50000-99999 214231 0.132723403 -2.019487995 -0.268033318 
1.791759469 
25000-49999 253650 0.1571446 -1.850588881 -0.290810049 H=1.767830194 
G=0.986644817 
10000-24999 325890 0.201899465 -1.599985405 -0.323036197 
5000-9999 183444 0.11364953 -2.174635869 -0.247146343 
SUM 1614118 1 1.7678 
 
 
 
193 
 
 
According to the principles of the Entropy Index, (G) is the value of entropy. If the 
rate tends toward the value (0), it means intensifying population agglomeration and 
imbalance in the population distribution. Suppose the value tends towards (1) or even 
more, so it means normal distribution of population and establishing a balance among 
the cities in an urban area. This study has tried to provide two levels of analysis to 
understand better what happened, how the current condition is, and how the 
population should be distributed concerning the size of urban area in the ideal form 
based on the results of Zipf's law.  
In Table 37, the cities are classified into different groups based on the population 
size in the first column. The second column showed the quantity of population and 
then calculated rate of [Pi: frequency, Ln (Pi) Ln Pi: Nehprii frequency logarithm, 
Pi*Ln (Pi)], and finally in the last column is showed the following information: 
These regulations and orders are applied to the other tables up to Table 63, which 
are analyzed based on Zipf's low. The classification of big and small cities and the 
population is based on the results of the Rank-Size role, which is accompanied by 
Zipf's analysis.  
In the 1986s, according to the presented results in Table 56, the amount of entropy 
is G= 0.755%, while according to the results of Zipf's law, it must be G=0.94%. It 
means there is no balance between the size of big, medium, and small cities and 
relative population agglomeration. The amount of Ln (Pi) for the cities with more 
population is lower than small cities and represents a concentration of population in 
the big cities.  
In the 1996s, the amount of entropy has decreased and was G=0.74% but mot 
considerably. According to the results, this decade continued the entropy trend, which 
started in the last decade with no considerable changes. Based on Zipf's law, the rate 
of entropy must be G=0.99%. In the 2006s, the rate of entropy has increased about 
G=0.85%, which should ostensibly show a few positive changes in the population 
distribution of this metropolitan area, but it is not valid in reality. What has made this 
result wrong is the increase of immigration to the first big city, which changed the 
194 
 
 
number of groups from 6 to 7 (K=7). It has a little normalized the final value of the 
entropy model. Because if we add the population of the first group to the second and 
fixed all changes that happened in the other groups, the rate of entropy would be like 
last decade G=738. In other words, all changes that have been occurred in the other 
groups of cities don't show considerable positive changes. But in this decade, for the 
first time, primary positive changes in this regard have happened in Medium-sized 
cities. And by the continuation of that, will be expected emerge of positive changes in 
the population mobility and redirection of migration follow instead of big cities to the 
Medium-sized cities. With respect to the results of the Ranke-Size Role, there is a 
substantial gap between the rank and size of the last small city with the first city. In 
comparison with the last decade, not only the rate of inequality has increased, even the 
population size of the first city became 1412 times bigger than the last city Table 60 
and Table 61. 
In the 2016s, as illustrated in Table 62 and Table 63, the amount of entropy is 
G=0.88, but unfortunately, this value, like the last decade, is not real and in 
accordance with the changes that happened in the other urban groups perfectly. Of 
course, in this decade, some positive changes started since the last decade in the size 
of populations in the Medium-sized cities. For the first time, five cities ranked in class 
B1, and it represented changes of movements to the other class of cities, what used to 
be one-sided and in favor of big cities (cities in class C1) Table 24. Also, the results of 
the Rank-Size Role have confirmed a reduction of the gap between the rank and size 
of the population in the small cities with fewer than 25000 dwellers compared to the 
big cities.  
 
 
 
 
 
195 
 
 
 
 
 
 
 
 
Chapter Nine 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
196 
 
 
 
 
Urbanization, development 
policies, and twelve decades 
planning practice, conflicts and 
lessons for Iranian cities 
 
 
9.1. Introduction 
This research has studied the urbanization and urban development process between 
1908-2021 to figure out the reasons for today's non-sustainable and polarized form of 
urban development in Iran. And the preliminary results of this study have shwon many 
obstacles and problems in urban areas that are structurally and refer to Iran's planning 
system, and in some cases, triggered by particular unwelcome social-economic and 
political changes. 
In Iran, urban governance has a significant dependency on the political system. 
Revolution and structural-functional changes in the political and social systems 
reformed urban management in Iran.  
Therefore, city management and urban governance of a place represent dominated 
political system, either open or closed, centralized or decentralized (Farzali Salari 
Sardari, Akbar Kiani, 2017). And for this case, urban management has a 
comprehensive linkage to Iran's centralized political system and structure. Such a 
centralized political-administrational structure has established a linear-vertical 
197 
 
 
relationship between the cities and state, which made the urban management 
inefficient and faced with many social-economic problems. In other words, 
centralization has intensified the presence of the government in the development and 
management of cities (A. Kiani, G. Fazelniya, F. Salari Sardari, 2013). Today, in Iran, 
several government ministries and agencies (at the regional and national levels) are 
the leading and influential directors of urban management and development Figure 
110. 
 
 
 
Figure 110 The conceptual model of the levels of urban management in Iran (by the author) 
 
Many structure problems in management and planning sectors have caused a 
systematic disintegration, especially in macro and micro levels of urban management. 
And inefficiency in urban management refers to the lack of appropriate political, 
social, financial, and legal bases, which has negatively affected public participation 
and declined citizens' role and rights in the decision-making process (Farnak 
Seyfoaldini, Mossa Panahandekhah, 2010). In Iran, the urban dwellers have never 
been questioned about their opinion during the planning and executing process.  
198 
 
 
For this country, many institutional and instructional problems have increased an 
unstable state of growth and unsustainable development, especially in the urban area, 
while declining polarization, the unequal form of urban growth, and urban 
development were defined as main goals in many national and regional development 
plans. It means the plans were not effective and successful. Also, polarized growth has 
intensified unbalanced demographic changes, and big cities have become bigger and 
bigger than medium and small-sized cities. Also, the development gaps between urban 
and rural areas became bigger and bigger (Hataminejad, Hossain, Zahra Zamani, 
Sadegh Hagineghad, Mohammad Ghazaee, 2010).  
According to the Iranian researcher, structural changes and corrections in the 
management and planning system are necessary to establish a decentralized system to 
enhance the role and power of urban dwellers in decision-making to solve or decrease 
urban problems (Mohammad Mirehei, Hossain Kalantarikhalilabad, 2011). Managing 
cities and organizing urban issues considering urban population growth and citizens' 
daily needs, especially in the big cities, is not more possible considering inefficient 
administration structures in Iran (Akbar Parhisgar, Ali Firozbakht, 2011, 8, 32). 
Generally, the political system and, of course, ideology, view, and politicians' 
attitudes play considerable roles in the planning, decision, or strategy-making process. 
Iran's municipalities are under the control of government agencies because of the 
centralized political structure. And the municipalities have no place in the urban 
decision-making process, and they are just executors of the government's policies. In 
Iran, the Interior Ministry, the Housing, Road, Urban Development Ministry, and also 
the Supreme Urban Development Council are the leading urban affairs directors 
(Elyaszazadehmoghadam, 2011). Additionally, more than six ministers, six presidents, 
and vice-presidents from other national organizations are directly and indirectly 
involved in the urban planning and decision-making process (Saeed Amanpor, 
Mahyar Sajadiyan, 2016). And municipalities must implement the desired plan and 
enacted by the responsible ministry (top-down view). It means municipalities are 
implementers of policies, providers of services, and not more. 
199 
 
 
This research has tried under a comprehensive analysis of Iran's urban management 
system and structure answers to the following questions: What changes happened in 
this country's planning and management structures, especially in urban planning 
between1908-2021? What factors and forces have accelerated emerging modern and 
contemporary urbanization in Iran? What forces have maximized centralization, and 
what consequences happened, especially for urban development? How can we realize 
a decentralized form of planning and management system in Iran, and why? 
9.2. The big bang of Iran's cities 
Iranian cities have faced substantial changes and transformations structurally, 
socially, also in content, rule, function, and population size over the past 120 years. 
And the Persian cities have been facing many problems, either natural and artificial 
environments, on a large scale. It is no exaggeration if say Iran's contemporary cities 
are like a package of urban problems in a showcase. The following table shows the 
changes in the political structure and administrational system, regulations, legislation 
regarding the urban discipline, and social-economic changes between 1908-2021.  
 
 
 
 
 
 
 
 
 
 
 
200 
 
 
Table 64 The trajectory of urban development in Iran and the main changes that happened between 1908 to 2021 (by the 
author) 
Types of implemented 
Types of Iran’s What have been taken place for the 
urban development Time 
political structure development of Iranian cities  
plans 
-Enacting the first urban legislations 
-Foundation of Balladdieh as the first local 
Persian government with limited tasks that was 
Constitutional responsible for: 1- Urban management - 1908 
Revolution 2- Increasing urban security and safty 3- 
Maintenance and repair of urban roads 4- 
Water management 
- Restructuring the national administration 
system 
- Development and amendment of urban 
laws 
- Fundation of Shardari as a new local 
government that was responsible for urban  
 
Reza Shah, the first management in urban areas but with more  
 
Pahlavi tasks than Balladdieh - Urban Road 
 
(Father Of Modern - Start of  the first urban development Development (Planning, 
 
Iran) plans at the national level Design, and 
1922-1942 
- Start of the modernization of cities for Constructing) 
the first time in Iran and stablishment of 
new and modern urban structures including 
publich transportation, health and 
education centers, making new roads and 
asphalt 
 
 -Infrastructural Development 
Mohamad Reza - Preparation of Urban Development Plan -Comprehensive Plan 
Shah, the second -Foundation Various Organizations -Detailed Plan 1942-1978 
Pahlavi Responsible for Planning and Control of  
 Urban Development 
 
- Abolition of land ownership 
After the revolution 
- Urban Land Organization 
1979 to the year - 1978-2021 
- Reducing the role of the municipality 
2021 
- Selling surplus building density 
201 
 
 
- Looking at the people at the lowest level 
- Enacted the law of the Cities Council 
- Add urban areas to big cities 
- Attention to the physical aspects of 
regional projects and lack of social 
participation 
 
Entrance to the new era of urbanization after the Persian constitutional 
revolution 
In this study, considering the trajectory of urbanization in Iran, this thesis has 
regarded happening the "Persian Constitutional Revolution" (Enghelab-e Mashruteh) 
as a Big Bang point and entering a new era of urbanization between 1905-1911 
(Ahmad Poorahmad, Hossein Hatamineghad, Seyed Hadi Hosseini, 2006). Because 
during the Qajar dynasty, this revolution had reformed the political structure and led 
to the establishment of the first Parliament in Persia7 in 1906. After the revolution, 
new changes had been emerged in all aspects (political, social, cultural, and 
economic) at the national levels, particularly in the cities.  
This study has regarded this revolution as a significant milestone in Iran's social, 
political, and economic history during the last century. The social, political, and 
economic elements and forces of the revolution had reformed Persian cities' patterns 
and structures (Dr. Ali Shamaei, Mohammad Mehdi Abrari, 2013). This time is 
regarded as a transition phase for the cities from urbanization with Persian orient to 
new urbanization with new characteristics. Accordingly, the pace of urban changes 
and development had accelerated surprisingly. After the revolution, many 
implemented policies and actions regarded as a base model for developing Iranian 
cities (Emamali Shabani, Jamal Kamalyab, 2012). For example, after the revolution, 
members of the first parliament enacted the first urban laws for providing better 
                                              
7 In the Western world, Persia (or one of its cognates) was historically the common 
name for Iran. In 1935, Reza Shah Pahlavi asked foreign delegates to use the term 
Iran, the endonym of the country, in formal correspondence. 
202 
 
 
services to urban dwellers, such as health services and water supply, by using a water 
tank Figure 112. In June 1907, enacting new urban laws led to the foundation of 
Balladdieh in the major cities (an organization that is responsible for urban affairs). 
Balladdieh was the first independent or self-government urban organization. But 
unfortunately, the coup of 1920 had restricted the power of Balladdieh and must work 
under the power and control of the new government (Saeed Amanpor, Mahyar 
Sajadiyan, 2016).  
 
Figure 111 Members of the first Iranian Parliament8 (Library W. D., 1906) 
                                              
8 This photograph shows the representatives of the first Iranian Majles (parliament) 
in front of the military academy, which served as the first parliament building. In the 
1870s–early 20th century, leading political figures in Iran concluded that the only way 
203 
 
 
 
 
Figure 112 Supplying water using water tanks (Najafzadeh, 2021) 
 
 
 
                                                                                                                                            
to save the country from government corruption and foreign manipulation was to 
make a written code of laws, an attitude that laid the foundation for the Iranian 
Constitutional Revolution of 1905–7. The movement for a constitution bore fruit 
during the reign of Muẓaffar ad-Dīn Shah of the Qajar dynasty, who ascended to the 
throne in June 1896. Under relentless pressure from the proponents of constitutional 
rule, Muẓaffar ad-Din Shah was forced to issue, on August 5, 1906, the decree for the 
constitution and creation of the elected Majles (National Consultative Assembly). On 
August 18, 1906, the first legislative assembly, the Supreme National Assembly, 
gathered in the national military academy to prepare for the opening of the first term 
of the National Consultative Assembly and to draft a parliamentary electoral law. On 
October 7, 1906, the shah inaugurated the first session of the Majles (October 7, 
1906–June 23, 1908). The most important task undertaken by the first Majles was to 
draft and ratify the constitution, which was completed on December 30, 1906. This 
session also established the internal procedures for the Majles and drafted and ratified, 
on October 17, 1907, the constitutional amendments 
204 
 
 
 
Figure 113 Lalehzar Street, Tehran in 1926s. (Gheissari, 2011) 
 
 
Figure 114 Persian Shops, 1905. A peep into the bazaar of Isfahan. In these open shops, all goods are exposed to view, 
and the passer-by is invited to take a seat and inspect (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) 
205 
 
 
 
Figure 115 A Street in Kerman, in 1907 leading into the long covered bazaar (Mary Hume-Griffith, Dr. Albert Hume-
Griffith, 1909) 
 
 
Figure 116 A bazaar in the city of Mashhad (Sykes, 1921) 
 
206 
 
 
 
Figure 117 A house-building project in Persia, 1904s, (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) 
As the above picture shows, the house was built normally from sun-dried earth 
bricks and chopped straw and then plastered. The bricks were generally made on-site. 
The main urban policies implemented by the Persian constitutional revolution:  
1. Control and management of urban market 
2. Collection of public tax and rents 
3. Legitimizing the property rights of landowners and feudal in the cities to 
transfer added value of the agriculture sector to the cities and 
commercialization of agricultural products in the cities (base of the rent-
capitalism and unequal development theory from Hans Bobek) (Bobek, 1974) 
4. Accumulation of capital in the cities through the auctions  
5. Legitimizing cities and their functions rather the non-urbanized areas and 
supporting cities through the urban laws (Ehlers, 1978) 
207 
 
 
6. Outsourcing and handing over control of public services to private enterprises 
and people; such as supply water, fuel, education, and healthcare (Balladdieh 
was irresponsible in the provision of the above services)  
7. Construction of public buildings such as Ab-Anbar9, Mosque, and Public baths  
8. Renovation of towers, city gates, and roads (Library N. P., 1905) 
 
 
Figure 118: The interactions between politics, law, and spaces (by the author) 
 
New urban evolution after the foundation of the Pahlavi dynasty  
Reza Shah10, the founder of modern Iran  
The new political structure was established by the Persian constitutional revolution 
but was stabilized after the foundation of the Pahlavi monarchy by Reza Shah Pahlavi. 
He is the "Father of Modern Iran" and has tried to develop and apply a new form of 
city-building through his modernist and reformist ideas and policies (Alireza 
Seyfzadeh, Mansor Badrifar, 2008). Iranian modernized and reformed cities resulted 
                                              
9 Ab-Anbar (Persian: آب انبار, literally "water reservoir") is a traditional reservoir or 
cistern of drinking water in Greater Iran in antiquity. 
10 (Reza Shah the First Pahlavi and her son Mohammad Reza Shah the Second 
Pahlavi) 
208 
 
 
from the modernist and reformist ideas of Reza Shah Pahlavi. The structure, form, 
pattern, and system of today's Iranian cities follow a trend and policies that he had 
launched for the first time in 1933 (Eckart Ehlers, Willem Floor, 1993). 
As mentioned above, owing to the coup of 1920, which had once powered 
centralization and Balladieh was not more independent. But Reza Shah has tried to 
increase the power of Balladieh by giving new tasks to work more efficiently. He has 
changed the name of Balladieh to Shahrdari and ordered to enact new urban 
legislations and develop urban laws. The "Law of Balladdieh" was abolished and 
replaced by enacting "New Municipal law" In 1930. On the one hand, for the first 
time, this law helped to establish "Shahrdari" (municipality) for the first time in the 
cities and towns in the whole of the country (Emamali Shaban, 2012).  
At that time, Iran was faced many problems as follows: 
 In terms of political power, Iran was unstable and under the control of colonial 
powers. Southern Iran was in the hands of the British, and northern Iran was in 
the hands of the Russians, and they had exploited the country's resources  
 Iran's economy had collapsed entirely, and poverty had spread throughout the 
country 
 Cities and villages had no health facilities and other basic infrastructures and 
facilities.  
 
Tehran of the 1890s is a prime example of the unsanitary condition observable 
throughout urban centers in the Qajar era Figure 119. For example, Iran was faced 
infectious diseases such as plague and cholera, and hundreds of thousands of people 
were dead. Dirty streets, stagnant and contaminated pools of water, and a suffocating 
atmosphere characterized its scorching summer months (A.Afkhami, 1998). Or, in 
1918, in the province of Khorasan, for example, the city of Mashhad had two-thirds of 
its 100,000 citizens sick with the flu. The epidemic killed about 3,500 people in that 
area: a 5% mortality rate within city limits and 7% in outlying villages (Afkhami, 
2003). 
209 
 
 
 
Figure 119, Panorama of Tehran, in 1892s, (Curzon, 1892) 
 
 
Figure 120 Royal square at Isfahan, in 1909s, (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) 
210 
 
 
 
Figure 121 The city of Isfahan from the north side (Sykes, 1921) 
 
 
Figure 122 Panorama of Shiraz, in 1909s. (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) 
 
 
211 
 
 
 
Figure 123 Mashhad, the sacred city of Persia. The picture was taken from the city wall and shows the mosque of 
Gauharshad (left), and the golden dome (center) in the background (Sykes, 1921) 
 
 
Figure 124 The Amirchakhmagh square in Yazd city (Sykes, 1921) 
212 
 
 
 
Figure 125  Tabriz city (Sykes, 1921) 
 
So, that was a supportive plan from Reza Shah to construct health infrastructures in 
the urban area to give service to urban and even rural. The new law had increased the 
government's role in the urban development process. In this regard, the government 
officially delegated the management of cities to the "Shahrdari" (municipalities) but 
under the authority of the interior ministry. 
In the Persian urban dictionary, the word "Shahrdari" is equivalent to 
"Municipality" and is a modern organization to direct and control urban growth and 
development. Emerge of "Shahrdari / Municipality" is also resulted from Reza Shah's 
modernist ideas. 
His first reform for urban development plan included the following actions:  
213 
 
 
- the foundation of needed urban organizations to better management, control, 
planning, and direction of urban development,  
- new and modern city building beside historical textures (broader and longer 
streets, asphalt roads, and railroads) 
- substantial changes in the roads and transportation system,  
- providing safer and faster accessibility between cities through the construction 
of asphalt roads and railroad at the local, regional and national levels  
- provision of new services and urban infrastructures. 
- Supporting industrial activities and building new and mother industries around 
the cities at the local, regional and national levels 
- improving the education system and constructing public and free universities 
for all people 
 
Figure 126 Constructing new roads in the city of Tehran by Reza Shah in 1946  (Mohammad Reza Pourzargar, Parichehr 
Moafi Ghaffari, Maryam Amjadi, 2018) 
 
214 
 
 
 
Figure 127 Providing water infrastructures in the city of Tehran city by Reza Shah in 1945 (Mohammad Reza 
Pourzargar, Parichehr Moafi Ghaffari, Maryam Amjadi, 2018) 
 
The modernization and reconstruction of Iranian cities were started in 1931 
broadly. The enactment of the new law of "Urban Road Development (Planning, 
Design, and Construction)" in November 1933 had provided a legal base for the 
government to apply new revolutionary city design in the oriental structure of Persian 
cities. Constructing new streets and roads has developed transportation networks and 
promoted the use of cars in the cities substantially. Furthermore, constructing big 
squares accompanied by massive office buildings were regarded as symbols of a new 
powerful empire and presented Iranian cities in a new and unique landscape and 
identity.  
Before the Pahlavi era, most Iranian cities were surrounded by enormous walls, 
defense tools, and city gates. However, modernization and reform ideas transformed 
215 
 
 
the Persian city from a closed-form to an open-form. Modernization had destroyed the 
cities' defense walls and gates, expanded city borders, and contributed the people to 
buildup and living outside of the destructed borders. 
 
 
Figure 128 The walls of Tus city (Sykes, 1921) 
 
216 
 
 
 
Figure 129 Dowlet gate, Tehran 1902 (Mary Hume-Griffith, Dr. Albert Hume-Griffith, 1909) 
 
Figure 130 The Mosque gate, City of Kerman (Sykes, 1921) 
217 
 
 
In cities, they were constructed and provided modern service systems and facilities 
for the first time, including a new transportation system such as Bus, Taxi, and 
tramway. New facilities included: piped water, electric lighting, Telephone, sanitation, 
drainage, and consequently, these actions increased new job opportunities and 
population growth.  
 
Figure 131 City Building in a new and modern form (left), under Pahlavi Dynasty, city of Tehran (by the author) 
 
 
Figure 132 City Building in a new and modern form (left), during Pahlavi Dynasty, the city of Shiraz (by the author) 
218 
 
 
 
Figure 133 Design and layout of public squares in new towns during Reza Shah Pahlavi (Eckart Ehlers, Willem Floor, 
1993) 
However, the planning system's structural change was in its primary stages of 
forming and needed time to fix the unpredicted shortcomings. There were no 
systematic coordination and task divisions among the organizations to perfectly direct 
and implement urban development projects. So, it was required to provide new 
structures to realize coordination between the organizations and activities 
substantially. Between 1935-1936 talk about providing a national development plan 
has increased in the parliament. The parliament had stressed restructuring the current 
traditional administration and planning system to a modern and efficient form. This 
trend led to the "Economic Council," founded in 1937, responsible for providing the 
first National Development Plan. But in this process, some significant factors had 
prolonged the planning process and included: 1) lack of experienced people, 2) lack of 
stable political power and sovereignty, 3) the start of the second world war and its 
shadow on Iran (National Bank of Iran, 1948).  
Most implemented urban development strategies between 1920-1941 focused on 
the public spaces and sidewalks in terms of content and physical. However, 
constructing new sidewalks, health centers, public buildings, providing urban 
furniture, and many other new services was considered as one of the most critical 
actions and positive aspects of urban design accomplished by municipalities for the 
following reasons: 1) Social-economic developments 2) to develop living conditions 
3) Industrialization and consequently migration (National Parliament Library, 1949). 
219 
 
 
The "Law of Urban Roads Development" was amended in July 1941 to accelerate 
urban development. But, implementing the newly amended law coincided with the 
Second World War and Iran's occupation. And this problem stopped the 
implementation of relevant urban development policies regarding the new law for 
several years. Anglo-Soviet invasion of Iran faced the country with a dramatic 
condition insofar as led to Reza Shah's abdication and was forced into exile by the 
invading British. The king's son Mohammad Reza Pahlavi came to the throne.  
After the war, the second king was resolute to allocate needed requirements for 
providing a National Development Plan, which encompassed urban and rural 
development strategies, in 1946. For this purpose, a national centralized and 
comprehensive planning system was structured and organized many economic and 
planning teams that included Iranian and foreign experts' "Harvard Group." In 
December 1946, signed a contract between Iran and "Morrison-Knudsen International 
Company" from the USA with the incorporation of "Overseas Consultant" to prepare 
the first national development plan on "Seven-Year Development Plan for the Plan 
Organization of The Imperial Government of Iran."  
Studying and analyzing these plans became necessary for this research. And it 
helped to understand what goals the government was pursuing in these plans, what 
social-economic strategies were implemented, and how these policies affected the 
cities. 
Urban Areas
Settlements
Rural Areas
Min
Economic Sectors Industry
Agriculture
 
Figure 134 The sectors that are under effects of the national development plans directly and indirectly (by the author) 
220 
 
National Development Plan
 
In the 1946s, Iran was in the preliminary stages of social-economic development 
planning. All urban development strategies and policies were integrated into the 
national development plans from the first to the third. And in the third and fourth 
national development plans emphasized preparing an especial development plan for 
the urban areas as a goal. In this regard, gathering and creating needed data and maps 
for providing development plans particular for cities was started in the third national 
development plan. As a result, the first Comprehensive Plans for some Iranian cities 
were provided during the fourth national development plan. 
 
Table 65 The main national implemented urban development policies between 1947 to 1987 (by the author) 
Development Goals and strategies of urban development during the Pahlavi 
Plan Name status 
periods Dynasty 
- Urban and Social reforms 
- Constructing cheap homes and apartments 
- Credits to the cities for supply piped water, use 
The first 
of mineral waters, and establishment of new electric 
national 
generators systems 
development 
- Profligacy actions and public health 
plan: 
improvement 
"Seven-Year 
- Increasing citizens' skills and ability, growth of 
Development From 1947 to 
Implemented education among the citizens, and supporting technical Plan for the the middle of 
1955 institutions in training skilled staff Plan 
- Increase of new job opportunities 
Organization 
- Giving advice and increasing technical 
of The 
knowledge of agricultures and Industrialists 
Imperial 
- Mapping and providing base maps for urban 
Government 
development planning 
of Iran" 
- Creating the first local, regional and national 
senses data bank 
- And the other development projects 
- Developing urban areas for support and rise of 
The Second 
From the production and export through building new factories 
National 
Implemented second half of - Developing public health service  and 
Development 
1955 to 1962 accessibility to healthcare and sanitation 
Plan 
- Social-cultural Development 
221 
 
 
- Increasing income levels and improve the well-
being of urban dwellers 
- Priority over urban development projects, 
improvement, and development of urban infrastructures 
such as asphalt 
- Growing transportation alternatives and 
developing transportation networks 
- Coordination between the urban organizations 
and activities 
- Implementing the Urban Road Network Design 
and City Networking Plan 
- Priority over the non-development regions facing 
climatic and geographical difficulties and providing needed 
infrastructures, services, and facilities included: piped 
The third water supply system, electric network, telecommunication 
From the 
national 
Implemented network, sanitation, technical and non-technical supports second half of 
development and s housing supply 
1962 to 1967 
plan - Credits to the not complicated development projects that 
were allocated from the second  development plan 
- Providing and creating maps for urban planning 
- Providing Comprehensive Plan for cities 
- Decentralization and share of development at 
the national level 
- Priority over the non-development area and 
providing infrastructures, services, and facilities 
- Education and urban management improvement 
- Building and providing cities infrastructures 
- Financial and non-financial supports to the 
The fourth 
municipalities to implement development projects 
national From 1968 to 
Implemented - Providing Comprehensive Plan for 46 cities 
development 1972 
- Providing needed maps by mapping for 
plan 
comprehensive plans 
- Education and urban studies 
- Help and support of municipalities in the urban 
management process 
- Analyzing and monitoring urban development 
plans 
 
222 
 
 
 
- The increasing rate of income 
- Mobilizing Army Science Board to provide 
opportunities for all people, even for people that are 
living in the most remote areas  
- Developing education and communication 
systems for both urban-rural areas 
- Developing health networks, especially among 
the low-income families  
The fifth - Family planning, increasing public awareness 
Not 
national From 1973 to about new methods to do that effectively 
implemented 
development 1978 
completely - Increasing public awareness about an order, 
plan perseverance, professional conscience, and drawing 
public attention to have active participation, especially 
among young groups in the development projects. Also 
inviting all associations at the local and regional levels to 
mobilize the public for this aim 
- Organizational development and developing 
service in both urban-rural areas  
- Providing new modern technical and logistical 
support for the municipalities  
 
 
9.3. Pervasiveness systemized and principled urbanization  
Consolidation of the second Pahlavi's monarchy king, "Mohammad Reza Shah," 
had accelerated urban planning activities; hence, amendment and enactment of urban 
law became necessary (Mojtahedzadeh G. , 2019). And the parliament, in 1960, had 
enacted a new legal bill on "Land Tenure" to remove legal barriers and accelerate 
urban development projects such as constructing new infrastructures and revitalizing 
old quarters in the cities. The legal bill was reenacted with a new title on "Urban Road 
Network Design and City Networking" in 1962. Accordingly, Iran's interior ministry 
had signed a contract with an American consulting firm. Then the first team of 
American experts under the title "Peace Group" came to Iran. They have planned and 
designed urban road networks for most Iranian cities and towns (Shieh, 2003).  
223 
 
 
   
 
  
   
Figure 135 Modern Tehran during Pahlavi Dynasty (Siyavosh, 2013)  
 
These applied novel ideas for developing Iranian cities coincided with the growth 
of technocrat and modernist thoughts in western countries. Capitalism and 
industrialization trends have conquered Orient urbanism's spirit and physics and 
reformed Iranian cities' traditional construction (Habibi, 2018). 
Hence, the Comprehensive Plan was gradually applied to the Iranian cities. While 
this plan initially was provided for western cities, especially for American cities, and 
was supplied according to the western countries' urban design patterns and rules 
(Dehaghani, 1994). It should be noted that today both the "Comprehensive Plan" and 
"Detailed Plan" are two main plans for directing Iranian cities' growth and 
development. Still, these plans are reviewed every ten years, while this plan in western 
countries is not more effective and replaced by "Strategic Planning" or other plans that 
224 
 
 
increase public participation (Behzad Malekporasl, Millad Alimohammadi, Sadegh 
Katoziyan, 2014). 
During the second development plan (1955-1962), for the cities, Isfahan, Sanandaj, 
Bijar, and Oromieh, were provided the Comprehensive Plan based on the "Point Four 
Program" by the American experts. Furthermore, during the third national 
development plan, they had provided the Comprehensive Plan for 17 cities 
(Rahnamaei, 2017).   
 
 
Figure 136 Iran's annual economic growth rate 1960-2019, (worldbank.org, 2021) 
 
According to this study, during the third development plans' planning, the 
government had tried to decentralize and reduce the top-down dominance in the 
decision-making process (Ali Shamaee, Mohammadmehdi Abrari, 2015). For the first 
time, the government had enacted a new bill, which allowed the regions’ authorities to 
provide development plans independently under supports of the national "Plan 
Organization." It has provided possibilities for implementing development projects 
independently at the regional level according to the principles of the Plan 
Organization. Such as constructing new roads, institutions, health centers, economic-
social development projects, etc. In my regard, it should be regarded as the first 
official action towards a decentralized planning system after the coup of 1920 in Iran 
(Naser Barati, Mina Barati, 2011) . 
In this era, while the new and young form of urban development was still in the 
formation and realization process, simultaneously, the government tried to change and 
225 
 
 
develop the urban municipal legislation and regulations. For instance, the "Low of 
Amendment of Some Articles and Add Some New Paragraphs to the Municipal 
Legislation" was passed in 1334 to attain the following selected goals: a) providing 
needed regulations and legislations to enhance effectivity and efficiency of urban 
development plans, b) providing new principles, guidelines, and standards for urban 
development plans, c) determining jurisdiction and municipal boundaries of cities, d) 
Monitoring and controlling buildings according to the Building permit and Blueprints 
(Shieh, 2003) (Zanouz, 2016). 
 
Figure 137 The percent of amendments or enacted urban development legislation and regulations between 1280-1359 
(by the author) 
 
The above actions had accelerated the pace of growth in the agricultural, industrial, 
economic, and service sectors and caused substantial changes in the urban-rural 
networks and interactions. The economy's dependency on the single-product "Oil" and 
revenue by selling crude oil had played a significant role in this trend. Single-product 
economics reformed the traditional spatial interactions between cities and the rural at 
the regional and national levels and tremendously accelerated these changes. Because 
had decreased dependency of cities on the rural products, consequently reduced the 
trade rate between the cities and rural areas (Nazarian, 1994). The government 
received millions of dollars of money every day by selling crude oil. At that time, the 
country faced financial problems and negative consequences of the Second World 
226 
 
 
War; the oil revenue had injected millions of dollars into the economy to start the 
engines of growth and execution of big development projects. And cities with more 
population, educated people, and other potentials became the places that could play a 
considerable role to help the government for realizing development projects. The 
cities became the main hotspot zones of economic activities. So, the government had 
started to reconstruct the Persian cities by the oil revenue. Finally, the era of 
contemporary Persian cities emerged in a modern form, contrasting with the old 
Persian cities' nature and texture.  
Some main factors, such as the a) nationalization of the Iranian oil industry, b) the 
White Revolution (Enqelab-e Sefid), which led to the land reform, and c) rise of oil 
price have increased the rate of investments in the urban area and by growing 
infrastructure projects in the cities and strengthening the urban economy emerged a 
deep gap between the urban and rural areas (Shokouei H. , 1992). 
After the Revolution of 1978 to Today 
In the early years of the revolution in 1978, the new government couldn't control 
and manage the market. It had turned the management and development of urban 
areas, especially the cities, into chaos and grown a form of city-building under a new 
policy Maskan-e enghelabi (Revolutionary Housing), immethodical and contrary to 
the rules (Zanouz, 2016). This revolution had fundamentally transformed the 
monarchy system and structure into a centralized republic system. The interior 
ministry and the Housing and Urban Development ministries dictate all urban 
development policies to the municipalities. The municipalities have no power to do 
everything without permission from the ministries (top/down or hierarchical 
relationship) (Asghar Nazarian, 2008). 
And today, all organizations involved in urban development and management 
couldn't plan and implement an urban development plan perfectly. Also unable to 
establish an integrated urban management system. As a result, today's cities have 
experienced a few corrective measures but temporary and scattered accompanied by 
turbulence, test, and failure (Mahnaz Hosseyni Siahgoli, Mostafa Ghadami, 2016). In 
227 
 
 
1984 the parliament enacted the new law on "Urban Development, Spheres of 
Influence and Detailed Plans" to apply some changes in the guiding principles of 
urban design and planning and the approval process. Furthermore, a new organization 
of Building New Cities and Satellite Towns was founded to settle the surplus 
population of big cities, like bedroom communities (Ziari K. , Principles and Methods 
of Regional Planning, 2008). 
The post-war11 era, regarded as a turning point to start privatizing municipal 
services. The country was facing a financial crisis and had not enough budgets to 
support urban areas. So, the cities themself have to care to find new financial 
resources to implement development projects. That was a big shock that time for 
municipalities that had always been supported financially by the state. They had no 
experience and didn't know what to do at that time? or how to find new financial 
resources?  
According to the previous studies, the government's actions after the revolution 
concentrated more on using all mechanisms to increase the control and dominance of 
the government's body over the local and regional authorities and organizations. So, 
the urban development policies of the new government included:  
1. Control and accumulation of wealth and capital in the center by the 
governmental organizations 
2. Providing new facilities for commercializing the agricultural and industrial 
goods in the cities but irregularly 
3. Foundation and growth of government-owned banks through the 
commercialization of capitals in cities 
                                              
11 Iraq was starter of the war and invaded Iran in 1980. The war had damaged the 
economic sectors of Iran, destroyed the infrastructures in large scale and imposed 
many problems to the social sectors. After eight years the war ended in 1988. 
228 
 
 
4. An unequal competition between the government-owned organization and the 
private sectors in the field of urban economy and mainly concentrated on the 
following sectors: distribution of goods, speculation in the land market, and 
housing.  
5. Delivering some public services by the semi-government organizations or 
affiliated with the government have increased their dominance over the market 
and imposed additional costs to the families  
6. Imposing exorbitant costs to citizens for providing infrastructure facilities  
7. Privatizing some significant services, including public education, health, and 
insurance and imposing high costs to the families 
8. Expansion of the bureaucratic organization's framework and supplying new 
government job opportunities to the job seekers in the cities 
9. More attention to the urban development than the rural areas and consequently 
a) growth of migration from rural to cities b) decreased potentials of rural 
productivity c) and promoting consumerism in the rural area. In the past, the 
villagers were the producer of agricultural goods, and today they are more 
consumers of goods of urban areas that are most of them importing every day 
from other countries. 
10. Supporting the services and intermediation activities in cities as an easy 
solution for money circulation by the governmental agencies 
11. Inattention to provide new job opportunities in the rural area  
12. The concentration of cultural, social, and economic centers in the cities and 
increasing dependency of the rural to the cities to meet the above needs 
(Sarrafi, 2010) (Mojtahedzadeh G. , 2019) (Asghar Nazarian, 2008) (Habibi, 
2018) (Shokouei H. , 1992) (Ziari K. , Principles and Methods of Regional 
Planning, 2008) (Shieh, 2003) (Hadiyani, 2001). 
229 
 
 
Today, the relationship between government and cities is interest-oriented and is 
not sensible. Because in some cases, changing a village into a new town is usually 
requested from some persons and groups with considerable influence in the 
government's executive organizations, and not from most of the villagers 
(Zanganehsharaki, 2013). Today, statistics show that about 766 places have emerged 
as new towns after the revolution. Just about 25 cases of the total were constructed as 
a new city, and the rest resulted from the change of villages to new towns (Seyed 
Shamsoaldin Sadeghi, Loghman Ghanbari, 2017). 
 
Table 66 Number of rural areas that have changed into towns (National Statistics Centers, 2019) (by the author) 
1956 1966 1976 1986 2006 
1996-
Decades - - - - - SUM 
2006 
1966 1976 1986 1996 2016 
Number of rural settlements changed into town 73 101 123 116 400 319 1132 
The average rate of changing the rural 
%7.3 %10.1 %12.3 %11.6 %40 %31.9 100 
settlements into the city 
 
 
Figure 138 Number of rural areas that have changed into towns (by the author) 
 
230 
 
 
Table 67 Growth of cities and towns with considering the implemented development plans before and after the 
revolution 1978 (by the author) 
1956 1966 1976 1986 1996 2006 2016 
Before 
Decades - - - - - - - 
1956 
1966 1976 1986 1996 2006 2016 today 
TNC at 
the 
191 271 373 496 617 1012 1345 - 
national 
level 
TNC and 
 +80 +101 +123 +121 +395 +333 - 
towns 
The The The first The third 
second fourth national national 
national national developm developm
developm developm ent plan ent plan 
The first The fifth The sixth 
ent plan ent plan About one 1989- (2000-
Implemen national national national 
(1955- (1968- decade 1993 & 2004) & 
ted developm developm developm
1962) & 72) & without The The 
developm ent plan ent plan ent plan 
The third The fifth developm second fourth 
ent plans (1949- (2011- (2017-
national national ent plans national national 
1955) 2015) 2021) 
developm developm developm developm
ent plan ent plan ent plan ent plan 
(1962- (1973- (1995- (2005-
1967) 1978) 1999) 2009) 
Type of 
Mohammad Reza Shah Pahlavi12 Period After the revolution and emerge of the Islamic 
governme
(1941-1979) (38 years) Republic of Iran (1979- Today) (40 years) 
nts 
 
 
Figure 139 Numerical growth of cities and towns in Iran from Pahlavi dynasty between (1956-1976), to the republic Iran 
between (1976-2016) (by the author) 
                                              
12 He was the second and last monarch of the House of Pahlavi (Pahlavi dynasty). 
231 
 
 
During such a trend, the government has performed the role of the central employer 
directly. And the cities are the main operational bases for engineering the 
government's social and economic interests. The centralized government is now city-
oriented, and their political and economic interests have an organic linkage to the 
cities. Hence, the government doesn't like to stop the numerical growth of new towns 
and urban-rural migration, and using this trend helps to have more control over the 
markets and activities (Mozafar Sarrafi, Jamileh Tavakollimiya, Mehdi 
Chamanimoghadam, 2015). Over decades the job market is not good, and most of the 
job offers are short time and, in some cases, without pension. So, there is no job 
security. And in this condition, the government offers hundreds of official jobs every 
four years for election campaigns. And people for taking these jobs have to accept and 
follow the government's actions and policies. And for symbolic political events and 
anniversaries, they force millions of them to attend these events and be on the street. 
So, this is engineering, controlling, and reforming social behaviors according to the 
government's desires. That is one of the main reasons the government likes the growth 
of the urban population and emerged polarised urban-rural societies and has shared 
development resources between places unequal. 
The following issues had established an ineffective form of urban management and 
governance:  
 The collapse of Iran's traditional production system,  
 The influx of foreign goods and capital over the country,  
 The inflow of oil revenue as the primary source of the central government's 
income has played a significant role in the urban development process, 
economic activities, banks, employees' salaries, pensions, etc. (Nazarian, 1994) 
(Shokouei H. , 1992). 
The second and third national development plans' social, cultural, and economic 
policies between 1995 – 2004 have intensified urban changes. In this period, the 
government agencies tried to expand their ideologies over the country (Plan 
Organization, 1961) (Plan Organization, 1955).  
232 
 
 
For example, the parliament in 1998 changed the name "City Council," which was 
founded in the Pahlavi dynasty, into the "Islamic City Council" and applied new 
amendments (Latifi, 1376). Unfortunately, these recent amendments had limited the 
tasks and power of the municipalities. For example, in paragraph five, public 
participation in the development plans is allowed once central government agencies 
agree. In the new amendment, they have removed paragraph 30 from the primary law, 
which allowed the interior ministry annually to send abroad the employees at the 
whole the country to study and obtain information on urban planning and 
administration for a maximum of two years. That was a positive rule to give a chance 
to the employees to develop their knowledge and skills for urban issues, but this 
matter had no place in the amended law. 
An Analysis on the Planning Processes and Actions after the Revolution 1978 
Planning system as a constructer of the planning frameworks, director of the 
development process, depending on the type of political system can be centralized, 
semi-centralized, or decentralized. Planning frameworks determines hierarchies, 
functions, and roles in a planning system. Iran's centralized planning system has 
disturbed the inter-organizational connections and activities between public and 
private organizations. Hence, analysis of the planning system helps answer the reasons 
for the fail and inefficiency of urban development plans in Iran. But, it is required to 
know how the structure of Iran's planning system is?  What organization and groups 
are involved in the planning and executing processes? And what problems hinder 
Iran's planning system? 
Generally, in urban planning, it is necessary to study the interactions of a city to 
other places considering the economic and non-economic forces at the regional, 
national, and even international levels. And in this study, these forces are studied at 
both local and national levels. Iran's national development plan encompasses general 
attitudes, policies, and defined budgets for projects. From one side, the national 
development plans have been played a considerable role in urbanization. And from the 
other side, due to Iran's centralized administration system, so government plays a 
233 
 
 
central role in the development planning process. Hence, studying Iran's planning 
system at the national level helps better understand the government's role in urban 
development. 
According to the structuralism theory, a system structurally is not apart from its 
subsystems, and all parts effort for a common goal. Accordingly, urban planning is a 
subsystem of the national planning system. So, local urban development policies 
follow national urban development policies, and the forces and decisions at the macro-
level for this case (Shokouei H. , 2009). 
According to the results, one of the other structural problems is the diversity and 
multiplicity of involved organizations in the planning process. It has generated many 
challenges and obstacles during urban development planning. So, it is required to 
solve this problem for realizing urban sustainability. Rapid urban population growth 
through the dramatic interregional migrations from rural to the big cities, and negative 
consequences of an unstable political-administrative system on the economic sector, 
financial crisis, multiple economic structures (traditional, semi-industrial, and modern 
just in mother industries), and fail of the planning organizations have been affected 
negatively on urban development. In other words, the city is not an independent 
variable in this sense and has an extreme dependency on spatial, physical, social, and 
economic factors. This complex national issue, which has been surrounded the urban 
areas, doesn't give any chance to the Persian cities to solve the obstacles charged by 
the national political and planning organizations.  
To continue is provided pathology on Iran's planning framework and included the 
following sectors: 
- Pathology of the planning system 
- Pathology of the goals 
- Pathology of the enacting process of development plans 
- Pathology of the program monitoring and evaluation process 
 
234 
 
 
Pathology of the planning system 
The results have shown that Iran's planning system has no precise definition for the 
concept, dimension, and character of the word "Development" with a broad consensus 
to apply in any development plans. In most of Iran's development plans, "Economic 
Growth" was defined as a goal (Barmaki, 2014). However, if we consider "Plan" as a 
regulator and organizer tool to achieve specified purposes, employing the word 
"Economic Growth" as a plan's goal cannot be a clear and comprehensive definition in 
Iran's development planning. As a result, different understandings and interpretations 
for the word "Development" happened in the different periods. And still, it is a 
significant challenge for planners and authorities. 
This fact shows we cannot be optimistic about successfully implementing 
development plans until we reach a consensus on the principles and paradigms of 
development among the planners, authorities, private sectors, and NGOs.  
The other point is that the planning system always has been defined with a high 
degree of centralization. Thus, all general social, political, and economic policies have 
been defined by the central government's leaders, while they have the lowest 
interaction with experts in the planning process. And this behavior is in contrast with 
the planning act's nature. Coordination among all involved organizations and persons 
is required for planning, enacting, and executing development plans successfully. 
Researchers believe that decentralization and effective "mutual interaction" between 
public and private sectors increases resiliency and capacities in the urban development 
process locally and nationally. Unfortunately, centralization is continually promoted 
by the mains leaders to the national planning organization and then to the regions and 
locals authorities in the urban management act. Such behaviors and actions are 
contrary to what planners and economists have always pointed out on the necessity of 
decentralization in Iran's planning system. 
Lack of a "Futuristic approach" and long-term strategies are the other main 
shortages. This problem deflected these plans from its straight course. That's why the 
executives are impotent to provide all required applications for new imposed and 
235 
 
 
spontaneous changes from parties and finally unsuccessful planning (Mohammad 
Taghi Rahnamaei, Parvaneh Shah Hossaini, 2009). 
 
Figure 140 Interactions between organizations, authorities, and planners during planning practice in a centralized system 
(by the author) 
Pathology of the development plans' goals 
Analyzing the damages in Iran's planning system shows a conflict between the 
planners and authorities in the planning process on planning and executing concepts 
and disciplines. And this is one of the main difficulties that have played a considerable 
role in the fail of development plans. On the one hand, the Iranian planners have 
always tried to find and develop new development strategies for the socio-economic 
sectors. But, on the other hand, political factors like disagreements between parties 
have restricted the circle of supports for the proposed strategies planners. And these 
different opinions resulted in the change of the priorities of plans or postponed 
enacting or executing time. 
The centralized political and administrational structure has increased the presence 
of military organizations or closed to the government in the economic activities and 
monopolized the production cycle and market. And of course, urban areas, with the 
highest contribution in the economic activities, were affected substantially. Also, this 
problem has decreased the presence of private sectors in the economic activities and, 
as a result, has impaired the urban economic forces and performance. Therefore, the 
236 
 
 
cities in such polarized markets have no chance to realize development plans' goals. 
Because they have no power in organizing the market and urban economic activities, 
today, the nature of the economic structure is determined by the government agencies 
and some political groups close to the government.  
In continue, the government has started the privatization policies in 2005. As a 
result, the political groups close to the government have seized most of the mother 
industries and main financial companies (Atashbar, 2011). This unwelcome event had 
intensified centralization and increased the government's power, presence, and 
dominance in all social-economic sectors. 
Inattention to the economic sectors and social organizations like NGOs in the 
planning process is a significant shortage in Iran's planning and development politics. 
The other reason referred to the government's role in changing policies, strategies, and 
planning and governing manners. So, if they do not tend to the defined development 
strategies by planners; as a result, such contrasts will be affected on the plan 
implementation negatively. 
Moreover, the results have shown that the plans' goals did not define clearly. And 
the word "Goal" or "Goals" were employed in different forms in the development 
plans. For example, in a development plan, they have written "General Goals," in 
another one, "Contents or General Orientation," etc. Regardless this disagreement is 
between the planners or else, that's like the personalization of development plans or 
applying personal favors over such plans (Barmaki, 2014). Different approaches 
between planners and politicians permanently have blocked achieving a consonance to 
define the plan's goals. Because of parties' conflicts, each winner party that comes to 
power will not follow another party's plan or policies. That is like a circular rotation 
and without any aim. 
In some cases, heightened tension during the planning act resulted in some 
organizations being suppressed unfairly from the planning team, but the deprived 
organization was officially responsible for monitoring and provide development plans. 
For example, after the revolution in 1978, the urban development ministry decided to 
237 
 
 
use the Comprehensive Plan for development planning over the country (Nazarian, 
1994). And according to the law, the Economic Council was responsible for providing 
these plans. But because of the above problems, oppositions have deprived the 
Economic Council of the planning team. It should be noted that this council was 
founded in 1937 as the first planning core in Iran. And this council was the founder of 
the new planning culture and provider of its knowledge and principles for the first 
time in Iran. And today, there is no organization like the Economic Council to take 
this responsibility and realize coordination among the policies, plans, and actions 
(Barmaki, 2014). Instead, the foremost leaders and politicians determine what plan 
must implement and what organizations must execute without respect to the plans' 
goals and priorities. Such behaviors and views made development plans ineffective 
and meaningless.  
Pathology of the enacting process of the development plans (Structural) 
Unfortunately, based on the results, the parliament could not enact the most 
national development plans according to the time plan. Surprisingly, in some years, 
there was no plan to implement. In other words, the country had no plan. Please take a 
look at Table 68. 
Table 68 The enacted development plans after the revolution 1979 (by the author) 
The last deadline for 
Enacted and ordered to 
Number of Development Plans Send the plan to the Sent to the Parliament 
the administration 
parliament 
After the revolution up to 1990 
the country was without No Plan No Plan No Plan 
development plan 
The First Plan 1988-09-22 1988-06-16 1990-03-01 
The Second Plan 1993-08-23 1993-12-21 1994-12-11 
The Thierd Plan 1999-09-22 1999-09-15 2000-04-05 
The Fourth Plan 2004-09-21 2004-01-12 2004-10-07 
The Fifth Plan 2009-09-22 2010-01-10 2011-01-10 
The Sixth Plan 2015-09-17 2016-01-16 2017-03-04 
 
238 
 
 
 
Figure 141 Iran's GDP growth by decades 1960-2019, the graph provided by the author, and the data from 
(worldbank.org, 2021) 
The other problem is that the executive and legislative branches' scope of activities 
and tasks are not defined clearly. Because the scope of legal actions of the parliament 
about the change of development plans draft or bills is not defined clearly (Hamed 
Samarghandi, Seyed Mohammad Moosavi Tabatabaei, Pouria Taabayan, Ahmad Mir 
Hashemi, and Keith Willoughby, 2016). On the one hand, according to the law, the 
executive sector is responsible for providing development plans (Barmaki, 2014). And 
on the other hand, according to the law, the parliament has the right to apply "minor 
changes" in the development plans. But it is a general definition and not clear.  As a 
result, in many cases, the parliament applied many changes in the content of plans 
beyond minor changes and regarded as replanning and interference in the executive 
branches' duties.  
Pathology of the plans implementation process  
When the oil export exposes to an external shock, the oil revenue will decrease. So, 
reducing the government's revenue means facing reducing financial resources to 
execute development plans or projects. The single product economy and heavy 
dependency on crude oil revenue led to incomplete and unsuccessful development 
plans. In continue, this problem is explained in more detail. 
239 
 
 
Also, the other factor with substantial adverse effects on the financial resources 
referred to Iran's political behaviors, foreign policies, and how to communicate with 
the other countries at the international level. Ideological differentiation has always 
negatively affected the safety of the middle east and Iran's political stability. And as a 
result, countries or investors don't want to invest their money in an unsafe place. 
International sanctions on Iran to change the government's behavior are one of the 
prominent pieces of evidence for this claim.  
Please consider, Iran is ranked as one of the top leading countries based on the 
value of natural resources and has fifth place globally. But, unfortunately, these innate 
potentials never have been used efficiently for urban-regional or national development 
due to the a) lack of domestic financial resources, b) unstable market and political-
economic system, and c) lack of safe investment space for foreign investors.  
The other factors that have increased urban problems' inefficiency referred to the 
politicians' dialogs and the government's significant leaders (Barmaki, 2014). Their 
orders and guidelines have always strongly influenced the development plans' policies 
and strategies. They determine how and when such plans have to implement (at the 
macro level), while they have never participated in the planning process (at the local 
level). Unfortunately, the political conflict between parties is not limited to the 
parliament and law, even in implementing plans. Analysis of Iran's urban management 
has shown that urban management's structure and manner have permanently changed 
by changes in the political sector and the change of leaders and authorities.  
After establishing a new administration, the new state doesn't want to follow the 
action plans, policies, and strategies that were done during the last four years by the 
previous party in power. Instead, they want to implement new development plans and 
projects according to their party's interests. So, parties don't take care of the public 
interest. Such conflictual behavior means unaccountability, waste of time, public 
resources, opportunities, and threatening the future of the current and next 
generations. This is a dominant political culture and behavior generalized in all 
management and execution parts.  
240 
 
 
Pathology of the plans monitoring and assessment process 
After analyzing the development plans' determined legal frameworks, the results 
show that these acts haven't been taken seriously. For instance, after providing a 
development plan and formal notification to implement the plan, then the executive 
sectors from the Government body are responsible for implementing the plans. But 
these organizations, Instead of concentrating on the contents of development plans and 
providing requirements before executing, have always tried to speculate in the 
parliament about allocating more financial resources to implement selected projects 
from the annual budget (Barmaki, 2014).  
The other problem is that the Economic Council was suppressed from some official 
tasks, particularly planning. According to the law, the Economic Council was the 
leading organization responsible for planning, assessing, and monitoring all 
development plans' implementation processes (National Parliament Library, 1949). In 
2009 the government changed the composition of members, and tasks were 
restructured ineffectively, and the tasks were assigned to the other agency. In such a 
case, it seems the planning activity has no more place than must be considered usually 
and seems like an administrative ritual. If monitoring the development plans is very 
important, tasks and activities are overlapped and not clearly defined. The other 
problem is that the government agencies have never asked for feedback from the 
public and did not publish complete reports around all implemented development 
plans correctly and without delay.  
 
241 
 
 
Goals of 
Plans
Monitoring 
implementa Planning 
tion of freamwork
Plans Dimensions of 
Study on the 
Planning 
Practice in Iran
Execution Enacting 
process of process of 
Plans Plans
 
Figure 142 The dimensions of studying Iran’s planning system (by the author) 
 
The problems mentioned above and shortages at the significant level of the national 
management and planning sectors have been made development plans ineffective and 
inefficient at the city, regional and national levels.  
The results of one study on the municipalities' revenue and financial resources have 
shown, in Iran, there is a significant relationship between the government's economic 
policies and implementation of monetization policies such as selling surplus building 
density by municipalities in the cities (Latifi, 1376). The government, many times, has 
reduced financial support to the municipalities from 100% in 1983 to less than 5% 
Today (AleEshagh, Parisa, Hodavand, Medi, 2014). And today, the municipalities 
have many financial problems; thus, they have been sacrificed valuable urban 
resources and urban sustainability for financial interests.  
For example, they are parceling and selling valuable agricultural lands for new 
buildings or selling surplus building density to increase revenue. Both strategies have 
been threatening the sustainability of the environment and generated many 
242 
 
 
environmental problems (Ziari K. , 1997). And todays' cities are overcrowded and 
populated more than what planners define in the cities development plan. Moreover, 
selling surplus building density increases the number of inhabitants in a place, while 
infrastructures are not enough (Mojtahedzadeh G. H., 2006).  
Understanding Iran's political-economic structures have helped identify the origin 
of urban problems and what external factors negatively affected Iran's urban 
management system. Additionally, this study has analyzed the passed bills and 
implemented urban development policies that had been implemented during the first 
and second national development plans between 1988s-1999s.  
The law of the first development plan 1988s specified the following policies for 
urban development:  
- Realizing balance in the distribution of population, decentralization of activities in 
the Tehran city as a capital, and prevention of dramatic physical and population 
growth in the big cities 
- Ensuring parallel development accordance with the population centers, priority in 
reconstruction and renovation of war-damaged cities 
-Improving urban management and enhancing technical, financial, and executive 
potentials of municipalities to be independent financially 
In the general policies chapter of the plan, one of the central specified urban 
development policies was: 
provision of part of municipalities' financial resources through legal taxes on the 
buying or selling of real estate. 
In the executive chapter of the plan, one of the central specified urban 
development policies was:  
- Supporting municipalities to be independent financially ( Plan and Budjet 
Organiyation, 1988). 
243 
 
 
After the war, Iran faced dramatic financial problems because selling crude oil has 
decreased significantly, so there was not enough budget for all projects and 
organizations. That's one of the main factors that the government has started 
privatizing the municipalities at that time. That was a solution to save money for the 
projects (Qasemi, Mohammad; Fayazi, Mohammad Taqi; Javadi, Shahin, 1985).  
But realizing this idea was unfavorable at that time. How can privatize the 
municipalities quickly, without considering how the municipalities can give service to 
the citizens without enough financial budget? While municipalities initially have to 
provide services to millions of people every day! For more than five decades, the 
municipalities were under the support and a part administration before privatizing. 
And then, in a short time, set apart from the administration body and be independent 
just in terms of finance? As a result, instead of concentrating on their tasks and plans, 
the municipalities are captivated by financial problems today.  
After disconnecting the municipality from the government body, the first 
development plans' law emphasized finding new financial resources to increase 
municipalities' revenues. So, they have never planed to provide financial resources 
before the privatization of municipalities. As mentioned above, this is one of the main 
reasons that municipalities have been selling surplus building density, which faced 
Iranian cities with many additional new difficulties and environmental crises today. 
The law of the second development plan 1994s specified the following 
qualitative policies for urban development:  
- Foundation of Urban Councils to improve technical and execution abilities of the 
municipalities to be more independence 
In the general policies chapter of the plan, one of the central urban 
development policies was: 
- Providing new revenue resources for municipalities through imposing new taxes 
limited to the cities' official borders (Plan and Budjet Organization, 1994). 
244 
 
 
Making such incongruous policies and dissonant with reality turned the cities into 
unpleasant places. For example, the "Mehr Housing" project was launched in 2007 by 
the administration to provide cheaper buildings for low-income groups at the national 
levels, especially for the urban zones (Naseri, Ali Mohammad, Naqavi, and Ehsan, 
2017). But the administration did not allow the municipalities to comment on the 
locating, planning, and executing steps of this project (Meshkini Shahrokhi Far, 
Hossein Tahmasebi Moghadam , 2019). The researchers have done numerous studies 
on this project and have analyzed its effects on urban spaces. The most common 
problems that this study have enumerated are: 
- most of them are located in the wrong places,  
- used inferior materials with shallow stability during building,  
- lack of infrastructures and services concerning age groups,  
- lack of accessibility to the transportation systems, schools, health centers, and 
markets (Khalili, Ahmad, Haniyeh, Norallahi, Rashidi, Naeemeh, Rahmani, 
Maryam, 2015).  
Domination of centralization in all aspects of political, administrational, social, and 
economic sectors made urban management ineffective.  
Also, this sector's analysis results on planning and enacting urban development 
plans indicated an orderly behavior and a top-down view in the planning act. 
However, the methodologies of these projects have no compatibility with the 
administrational structure. In addition, the diversity of organizations has slowed down 
the planning and enacting process. The incompatibility of the ratifications for urban 
development plans with government institutions and organizations' budgeting methods 
is another problem in this field. 
In the first urban development plans, the government had sharply manipulated the 
contents of development plans. In contrast, many planners have criticized this act at 
that time. And today, not only don't want to stop this behavior, even have tried to 
separate their dominance in all sectors tremendously. Why? Because the base of 
245 
 
 
development panning guidelines and principles theorized as a government-owned plan 
in Iran (culturally and structurally). And should be noted, this is also one of the main 
reasons that the people have never been invited or asked to participate in the planning 
process.  
Some of the significant shortages of the centralized planning system and vertical-
sectoral structure of the national administration issued for this part as follows: 
- Lack of a national spatial development plan with a consensus among all 
involved organizations and guarantee a plan-based execution. An integrated 
form of the planning framework links the local and national organizations and 
coordinates activities.  
- Provide and enact local development plans (for the cities) by the ministries at 
the national level due to centralization, which contrasts with cities' priorities 
and potentials at the local levels. 
 
 
Figure 143 Numbers of enacted conperehencive plans for the development of Iranian cities (by the author) 
 
246 
 
 
 
Figure 144 Numbers of cities that have faced contradictions in both Comprehensive Plan and Detailed Plan (by the 
author) 
National Development Plan Urban Development Plan
Ambiguity in the nature and Golas Ambiguity in the nature and Golas 
Problem in planning and enacting process Problem in planning and enacting process
Inadequacy and executing problems Inadequacy and executing problems
 
Figure 145 The systematic direct effects of national plans on the local plans in a centralized system (by the author) 
 
9.4. Analysis of the contents of urban development plans 
As mentioned before, the theories, principles, and methodology of Iran's urban 
development plans were copied from the industrialized countries before the 1970s and 
never updated the contents and theoretical foundations of the development plan 
considerably.  
247 
 
 
Planners have consistently criticized these plans' methodology because those who 
provide a development plan have no role in the implementation process, while they 
have to monitor and control it.  
Belief in pure rationalism and making an absolute decision for cities' future were 
products of modernism and are doomed to failure initially, but such approaches 
applied to Iranian cities (Shokouei H. , 1992). This is the same problem in the 
industrialized countries, and today they are correcting or reconstructing some places in 
the cities that were building up incorrectly, particularly between the 1970s-1980s 
(Dehaghani, 1994).  On the one hand, these plans positively affect the zoning and 
building; on the other hand, these couldn't realize the specified goals in these (Ziari K. 
, Urban Land Use Planning, 2009). Today's urbanism in terms of social, technological, 
and economic changes contrasts with the past urbanization and Iranian cities planned 
based on the planning theories up to the 1980s. Today, after many decades of 
executing these plans in the cities, unfortunately, these plans are failed to satisfy urban 
dwellers, and often a tiny percentage of proposed land uses are realized.  
The results of a study on the Urban Comprehensive Plans that was done by Iran's 
National Planning and Budget Organization in 1993 have shown that most of these 
plans were unable to realize desired goals in practice. Also, more than 70% of 
population predictions did not occur. In 40% of the cases, the city development 
directions were in the opposite directions that were predicted in the plans (Plan and 
Budjet Organization, 1993). 
Moreover, proposed building densities are realized rarely in the cities. Land parcels 
and proposed per-capita lost their efficiency due to the failure to predict population 
(Goldis Vahidi Borji, Farshad Nourian, Mohammadmehdi Azizi, 2017). City 
Comprehensive plan is just physical oriented and can not solve social-economic 
problems (Keramatollah Ziari, Alireza Mohammadi, 1395). Today, after about six 
decades of implementing many comprehensive development plans in most Iranian 
cities and towns; however, these plans have failed to prevent the unbalanced and 
heterogeneous development of cities and provide solutions to manage urban growth 
248 
 
 
(Ali Zangiabadi, Mehdi Abdollahi, Roghayeh Salek Ghahfarkhi, Behnam 
Ghasemzadeh, 2014). 
Ambiguities and problems in urban development plan’s nature 
Unfortunately, the nature and contents of the urban development plans have not 
been localized and accommodated with Iranian cities' geographical conditions, 
especially according to its administrative structure (Ziari K. , Principles and Methods 
of Regional Planning, 2008) (Dalir, 2009). 
Because cities' problems and challenges are different in the same region, Iran has 
various geographical and environmental climates, features, and landscapes. Therefore, 
proposed solutions, strategies, and prioritizing are according to each city's problems 
and needs in its geographical-spatial location.  
Surprisingly, planning guidelines for all Iranian cities and towns are the same, 
without considering these geographical, environmental, spatial, social, cultural, and 
economic diversities (Nazarian, 1994).  
Also, the time-consuming and lengthy enactment process of development plans is 
the other main reason that faced predictions of the following sectors in most cases to 
fail included: social-economic projections, population changes, land-use changes, and 
urban growth. In some cases, just enacting a development plan has been taken 3 or 4 
years!  
 
249 
 
 
 
 
 
 
 
 
Chapter Ten 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
250 
 
 
 
 
 
 
Land Use Changes Modelling 
 
 
10.1. Introduction 
The importance of land use/land cover changes 
Land use/land cover change is considered as one of the most critical environmental 
issues of global concern (Iverson, 1988). Changes in land use/land cover and the 
associated habitat loss and fragmentation are significant causes of biodiversity loss 
(Erich Tasser, Ulrike Tappeiner, 2002). Such changes have been generated by human 
activities such as industrialization, urbanization, agriculture intensification, land 
degradation, and overgrazing (Bryan C Pijanowski, Daniel G Brown, Bradley A 
Shellito, Gaurav A Manik, 2002). These human-induced changes decline natural 
resources and led to severe social, economic, and political consequences (Balak, 
2003). 
These significant issues led to the emergence of many international 
multidisciplinary research projects to monitor and study Land Use and Land- Cover 
(LULC) changes (Thenkabail, P. S., Schull, M., & Turral, H., 2007) and Global Land 
Project (GLP) (Ademola K. Braimoh, M. Osaki , 2010). Both are joint projects of the 
International Geosphere-Biosphere Project (IGBP), launched in 1987 to examine how 
Earth's ecological processes interact at a broad scale and how they are affected by 
human systems (Smucker, 1998). Or an International Human Dimension Project 
251 
 
 
(IHDP) was launched in the 1990s to study global changes from the social perspective 
(Ola Uhrqvist, Eva Lövbrand, 2014).  
In this regard, also the availability of remotely sensed data and its advance in the 
temporal, spatial, and spectral resolutions have provided some possibilities to detect 
daily changes on the Earth's surface at different scales (T. V. Ramachandra, Uttam 
Kumar, 2004). Monitoring and understanding these dynamic land-use changes provide 
more accurate information, which can also help to meet better strategies in the 
decision-making process during the planning and managing steps (Lambin, Eric F. 
and Geist, Helmut J. and Lepers, Erika, 2003). Especially over the last three decades, 
various hardware and software have been developed for capturing and analyzing 
remote sensing data. Rogan and Chen, in 2004, have defined a new digital and/or 
detection system to describe land use/land cover changes based on the co-registered 
multi-temporal remote sensing data. The used techniques for assessing change were 
numerous and included both statistical and rule-based methods (Chen, J., Gong, P., 
He, C., Pu, R., & Shi, P. , 2003). 
Material and methods 
For the step of this analysis, this study has used time-series Landsat images from 
the 1972s by 2020s, as listed in the following Table 69.  
 
Table 69, The used time-series Landsat images (by the author) 
Timeline Processing correction level Bands 
1972.09.22 LM01_L1TP (6,5,4) 
1988.07.02 LM05_L1TP (3, 2, 1) 
1999.06.30 LE07_L1TP (4, 3, 2) 
2010.06.05 L7_ L1T (4, 3, 2) 
2020.06.24 LC08_L1TP (5, 4, 3) 
 
 
252 
 
 
Satellite Imagery Formats 
Band sequential with three bands, four columns, by four rows 
 
Band-interleaved-by-pixel with three bands 12 columns by 4 rows (Clarklabs, 
2020) 
 
Geographic Database Concepts 
The used time-series Landsat images  
   
Figure 146: Landsat image of the 1972s Figure 147: Landsat images of the 1988s  Figure 148: Landsat images of the 1999s  
(USGS, 2021) (USGS, 2021) (USGS, 2021) 
  
Figure 149: Landsat images of the 2010s  Figure 150: Landsat images of the 2020s  
(USGS, 2021) (USGS, 2021) 
253 
 
 
 
Classifying the Images 
 
Figure 151: The defined color ranges for the land covers (Clarklabs, 2020) 
 
10.2. Maximum Likelihood 
The MAXLIKE module has provided the Maximum Likelihood procedure in the 
IDRISI Image Processing toolset to compensate for the main deficiencies of both the 
Parallelepiped and Minimum-Distance-to-Means procedures. The Maximum 
Likelihood procedure is based on Bayesian probability theory. The MAXLIKE 
module uses the mean and variance/covariance data of the signatures to estimate the 
posterior probability to determine which pixel belongs to predefined classes 
(Clarklabs, 2020). 
In many ways, the MAXLIKE module is similar to the MINDIST with the 
standardized distance option. The only difference refers to the MAXLIKE accounts 
for intercorrelation between bands (Reveshty, 2011). MAXLIKE incorporates 
information about the covariance between bands as well as their inherent variance and 
produces an elliptical zone of characterized signature but conceptualized (Paul, S. S., 
254 
 
 
Li, J., Wheate, R., & Li, Y., 2018). In fact, it calculates the posterior probability of 
belonging to each class, where the probability is highest at the mean position of 
classifications and falls off in an elliptical pattern away from the mean (Parth Sarathi 
Roy, Lars T. Waser, 2017). 
10.3. The change prediction process in LCM 
Land change prediction in Land Change Modeler is an empirically driven process 
that moves stepwise from 1) Change Analysis, 2) Transition Potential Modeling, to 3) 
Change Prediction. It is based on the historical change of land cover maps from time 
point 1 to time point 2 to project future scenarios (Kshitij Mohan, Praveen Kumar Rai, 
Varun Narayan Mishra, 2014). 
The Land Change modeler interface is organized around a set of six major tasks: 
 Change Analysis: Analyzing past landcover change 
 Transition potentials: Modeling the potential for land transitions 
 Change prediction: Predicting the course of change into the future 
 Planning: Evaluating planning interventions 
 REDD Project: Estimating GHG emissions from REDD projects 
 Harmonize: Formatting land cover maps to use in Land Change Modeler (lab 
only launches when landcover maps are incorrectly formatted) (Clarklabs, 
2020) 
The landcover maps used by LCM must be formatted to meet the following 
conditions: 
1. legends in both maps are the same. 
2. Categories in both maps are the same and sequential. 
3. Backgrounds in both maps are the same and have a value of zero. 
255 
 
 
4. Spatial dimensions, including resolution and coordinates, are the same (R. K. 
Jain, Kamal Jain, S. Rehan Ali, 2017). 
 Change Analysis 
In Change Analysis, change is assessed between time point 1 and time point 2 
between two land cover maps. Identified changes are transitions from one land cover 
state to another. It is likely that with many landcover classes, the potential 
combination of transitions can be very large. What is important is to identify the 
dominant transitions that can be grouped, modeled, and termed submodels (Nidhi 
Nagabhatla, C. Max Finlayson, Sonali Seneratna Sellamuttu, 2012).  
10.4. Transition potential modeling 
The second step in the change prediction process is Transition Potential Modeling, 
where we can identify the potentials of land to transition. This step will create 
potential transition maps of suitability for each transition. In LCM, a collection of 
potential transition maps is organized within an empirically evaluated transition sub-
model that has the same underlying driver variables (Clarklabs, 2020). A transition 
sub-model can contain a single land cover transition or a group of transitions that have 
the same underlying driver of variables. These driver variables use to model the 
historical change process. For example, if you are modeling deforestation due to 
agriculture, river variables to consider would be slopes, proximity to roads, or 
previously deforested areas (Florencia Sangermano, J Ronald Eastman, Honglei Zhu, 
2021). Transitions are modeled using either a multilayer perceptron (MLP) neural 
network, logistic regression, or a similarity-weighted instance-based machine learning 
tool (Same Weight) (Rahim Aguejdad, Thomas Houet, Laurence Hubert-Moy , 2017). 
Once calibrated, the model is used to predict future scenarios. 
Change Prediction 
The third and final step in the Change Analysis is Change Prediction. Using the 
historical rates of change and the transition potential model, LCM can predict a future 
scenario for a specified future date. In its simplest form, the model will determine how 
256 
 
 
the variables influence future change, how much change took place between time 1 
and time 2, and then calculate a relative amount of transition to the future date 
(Clarklabs, 2020). To remake the model more robust, the Land Change Modeler 
allows for the incorporation of constraints and incentives, such as zoning maps; and 
planned infrastructure changes, such as new roads or land cover development. Driver 
variables can also be dynamic in nature so that at regular interim intervals, they can be 
recalculated and reenter the model (Megersa Kebede Leta, Tamene Adugna Demissie, 
Jens Tränckner, 2021). For example, you may have as one of your driver variables 
distance from previously deforested areas. This variable could be recalculated at 
regular intervals as and cover transitions from forest to agriculture. 
10.5. Hard classifying 
The distinguishing characteristic of hard classifies is that they all decide the 
landcover class to which any pixel belongs. TerrSet offers a host of supervised 
classifiers in this group. Some like (MAXLIKE) means maximum likelihood, and this 
procedure is unquestionably the most widely used classifier in the classification of 
remotely sensed imagery.  
10.6. Soft classifying 
Contrary to the hard classifier, the sot classifier does not decide the landcover class 
to which each pixel belongs. Instead, they develop statements of degrees to which 
each pixel belongs to each of the landcover classes being considered. Thus, for 
example, a soft classifier might indicate that pixel has a 20.72 probability of being 
forest, a .24 probability of being pasture, and a 0.04 probability of being bare ground. 
A hard classifier would resolve this uncertainty by concluding that the pixel was a 
forest. However, a soft classifier makes this uncertainty explicitly available for 
various reasons (Clarklabs, 2020).  
10.7. Markov model 
Markov model has been widely used in ecological modeling (Nouri, J., 
Gharagozlou, A., Arjmandi, R. et al. , 2014). Markov model considers past states to 
257 
 
 
predict how changes a particular variable over change modeling is promising because 
of its ability to quantify not only the states of conversion between land-use types but 
also the rate of conversion among the land-use types (Ye B., Bai Z., 2008). A 
homogenous Markov model for predicting land-use change is presented 
mathematically as follow; 
 
And 
 
where, L(t+1) and L(t) are the land-use status at time t+1 and t respectively. (0≤ Pij < 1 
and  Σm j=1 Pij=1 , (i,j= 1,2, … ,m) is the transition probability matrix in a state. 
10.7.1. Cellular Automaton Markov Model 
A cellular automaton model is developed to investigate its utility in constructing 
scenarios of future urban land transformations (Clarke KC, Hoppen S, Gaydos L., 
1997). CA-Markov model combines cellular automata, Markov chain, multi-criteria, 
and multi-objective land allocation to predict land cover change over time (BEHERA, 
M.D., BORATE, S.N., PANDA, S.N. et al., 2012). It adds into the Markov model not 
only spatial contiguity but also the probable spatial transitions occurring in a particular 
area over time. MARKOV and CA_MARKOV modules in IDRISI are used to create 
transition probability and transition area matrix (Adhikari, S.; Southworth, J., 2012). 
A transition probability matrix is obtained by cross-tabulation of two images of 
different times. It determines the probability of a pixel in a land-use class to change 
into another class during that time (Sylvertown J, Hotlier S, Johnson J and Dale P, 
1992). On the other hand, a transition area matrix contains the number of pixels 
expected to change to a land-use class from another class during a period.  
258 
 
 
 
Figure 152: The research framework for remote sensing and modelling (by the author) 
 
 
259 
 
 
 
Figure 153: The classification and reclassification of the provided landsat images (by the author) 
 
Land use/cover change 
 
Figure 154: The classified land covers change of Sari city for the year 1972 (by the author) 
260 
 
 
 
Figure 155: The classified land covers change of Sari city for the year 1988 (by the author) 
 
 Figure 156: The classified land covers change of Sari city for the year 1999 (by the author) 
 
261 
 
 
 
 Figure 157: The classified land cover changes of Sari city for the year 2010 (by the author) 
 
Figure 158: 2020 The classified land cover changes of Sari city for the year 2020 (by the author) 
 
262 
 
 
Table 70: Land Cover Changes of the Sari City, 1972-2020 (by the author) 
.Categories/Time series 1972 % 1988 % 1999 % 2010 % 2020 % 
44. 1216. 63. 1764. 72. 2234. 62. 3144.3 62.
BUILTUP 338.96 
77 08 31 7 77 69 19 6 72 
41. 26. 448.9 18. 1215. 33. 33.
VEGETATION 312.92 501.8 1674.2 
33 12 2 51 9 84 39 
12. 173.8 9.0 180.3 7.4 2.6 2.9
UNCULTIVATED LAND 98.28 94.32 146.52 
98 2 5 4 4 2 2 
0.9 1.5 1.2 1.3 0.9
WATERBODY 6.92 29.15 31.07 48.37 48.29 
1 2 8 5 6 
Sum of the area of the Sari city 1920. 2425. 3593. 5013.3
757.08 100 100 100 100 100 
(Hectares) 85 03 28 7 
“Residential density od Sari city and projected population growth for this city” 
 
Decades 1972 1988 1999 2010 2020 
Population predicted based on the 
60108 161878 209188 290262 390452 
Modified Exponential Model 
Gross density of the population 
79.39 84.27 86.26 80.78 77.88 
(Hectares) 
The total density of the residential 
177.33 133.11 118.54 129.89 124.18 
areas (Hectares) 
 
Table 71: Population of Sari City, 1976-2016 (National Statistical Center of Iran, 2017) 
Decades 1976 1986 1996 2006 2016 
The total of the population according to 
70753 141020 195882 259413 347402 
the annual data 
 
The above table illustrates the physical expansion of the built-up area over the five 
decades. This study not only has tried to study the land cover changes of the city and 
also has studied periphery areas that surrounded the whole of the city. It helps to 
understand better and compare the land cover changes and figure out how these 
changes are for each decade. But should be noted, the presented results on the above 
table just are closed to the area that, specifically for this case, is named symbolic as 
"calculated area" Figure 160. 
 
263 
 
 
 
Figure 159: The simple dynamic model of the growth of Sari city that follows nodes and road development  (by the 
author) 
 
Figure 160: The built-up area within of the official border of the city (by the author) 
 
According to the results shown in Table 71, the city has grown highly from 1972 to 
2020 and has been facing a continuation of sprawl form of physical growth Figures 9-
13. Area of the city under economic and social forces has been increased surprisingly. 
Concerning the results, just the city's built-up area in the 1972s was 338.96 hectares, 
and in the 1988s it expanded to 1216 Hectares, in 1999s became larger about 1764 
hectares. In the 2010s, the area has progressed to 2234.69 hectares, and finally, in 
2020s has expanded physically up to 3144.36 hectares Figure 165. According to the 
results, after five decades, today's city area is 9,3 times bigger than the area of the city 
in 1972 Figure 162.  
According to the annual data, the city's population was about 60108 in the 1972s. 
And the final results show that the Built-up area was 44.77% of the city's total area, 
and the rest area was occupied by other land uses such as (Vegetation, Uncultivated 
land, and Waterbody) Table 71. But in the following decades, the area of the built-up 
zone compared to the other land use has dramatically changed Table 71, Figure 163, 
Figure 165.  
264 
 
 
 
Figure 161 The physical growth stages of Sari city (by the author) 
 
 
Figure 162 The physical growth of the city of Sari considering all land uses from 1972 to 2020 (by the author) 
265 
 
 
 
Figure 163: Changes of the area of Sari city including: Built-up, Vegetation, Uncultivated and water body over the last 
decades (by the author) 
 
 
Figure 164 The physical growth of Sari city combined by the land cover changes from 1972 to 2020 (by the author) 
266 
 
 
After the 1972s, on the one hand, the city was faced with the dramatic growth of 
the built-up area, and on the other hand, the city lost the area of the other land uses, 
especially Vegetation. As is showed in Table 71, in 1972 rate of the built-up area was 
44.77% and the Vegetation 41.33%, and in 2020 respectively are 62.72% and 33.39% 
Figure 164. In this figure, by colors, hachure and lines is incredibly represented a 
tremendous area of non-developed lands that have been replacing with Built-up area 
Figure 164. The hachured symbol shows the Built-up area of the city in the 1972s, and 
the other land covers area around the city is presented by red, light green, dark green, 
and gold colors. It is hard to imagine how these valuable land covers have been 
changed and replaced by buildings and asphalt.  
Based on the results, the decade 1999 was one of the most dramatic times of land 
cover changes regarding these find out facts of this study that, the rate of built-up area 
was 72.77% and Vegetation 18.51%. It should be noted, according to the results of 
Elasticity Rate in chapter seven, between the "1986s-1996s," the city experienced the 
highest rate of elasticity from 1956 to 2016. It means the city has faced massive 
migration. Also, concerning the results of the "Isard Model" in chapter eight, between 
the 1996s, the city has experienced the highest rate of average Economic growth at the 
national level. Moreover, based on the results of the "Location Quotient Model" in 
chapter eight, in this decade, the city had been facing the highest rate of growth in the 
agriculture sector for about 1.209%. But in the service and industry sector rate of 
growth was not considerable. It means that the other forces are playing a role in this 
concept, such as economic polarization and expansion of a polar form of development 
at the national and regional level. The results of Rank-Size Role from 1986 to 2016 
have approved domination of four big cities (Sari, Babol, Amol, and Ghaemshahr) in 
the urban hierarchies of this region. In Iran, 1961s "Growth Pole Theory" for the first 
time applied in the third national development plan to reduce social-economic 
imbalance first at the national and regional levels then locals. Actually, these four big 
cities have to share of development to the other places to reduce economic imbalance 
and reduce migration from rural and towns to the big cities or other developing areas 
that have more potential in the supply of jobs and other services to the dwellers. But 
as a result, the outcomes or what today is going on in the urban area is in contrast with 
267 
 
 
the imaged goals of "Growth Pole Theory." According to the last annual data for the 
2016s, Iran has 1242 cities and towns with about 59,146,847 dwellers. Surprisingly, 
53.46% of urban populations are living just in 32 big cities with more than 250000 
populations; meanwhile, these big cities just accounted for 2.58% of the total Iranian 
cities Table 72. Definitively it shows centralization in the urban system and 
concentration of population in the urban area. Why? What forces and performances 
have made such types of development plans fail? About urban development plans and 
planning systems in Iran and given answers to the above question discussed 
particularly in Chapter nine. 
 
Figure 165: Physical growth of Sari city over the last decades (by the author) 
 
Table 72, The lassification of urban areas considering population, Iran (by the author) 
Size of the population of Number of cities Percent of cities Number of Percent of 
urban areas  and Towns and towns populations Population 
Urban areas with more 
32 2.58 31,620,670 53.46 
than 250000 
Urban areas with less 
1,210 97.42 27,526,177 46.54 
than 250000 
SUM 1,242 100 59,146,847 100 
268 
 
 
 
Figure 166: Changes in all land covers and comparison with each other between 1972-2020 (by the author) 
 
Table 73 Changes of land uses from one type to the other type (by the author) 
Percent of Converted to 
Types Codes Hectares 
area the type 1 
BUILTUP 1 522 12 % 1 | 1 
VEGETATION 2 3003.48 70 % 2 | 1 
UNCULTIVATED LAND 3 473.4 11 % 3 | 1 
WATERBODY 4 288.36 7 % 4 | 1 
 
 
269 
 
 
 
Figure 167 The graphical demonstration of land-use changes from one type to the other types (by the author) 
 
Today's dramatic land covers changes resulted from five decades of political, 
social, and economic changes and the implementation of numerous development 
plans. The above picture demonstrates how land cover types have been changed into 
the other types Figure 166. The left side shows the changes of each land cover with 
predefined codes from 1 to 4. For every kind of land use are defined a code. For 
example, the number 1 is issued to the built-up area. The number 2 is issued to the 
Vegetation, the number 3 for the uncultivated lands, and the number 4 for the 
Waterbody Table 73.  
According to the find outs of this study, after the 1972s, about 4287.27 hectares of 
land covers have been changed. This study has provided a transition map to better 
grasp how critical the intensity of these changes is. This map illustrates how the 
studied land covers around the city, such as vegetation, uncultivated land, and water 
body, have been changed into the built-up covers from 1972 by 2020; (see Figure 
168). In this map, the red color symbolizes the lost land covers, and the green color 
indicates the gained lands with the green cover.  
Surprisingly, the city has been lost about 3765.24 hectares of valuable lands with 
green covers, which changed into the built-up areas, approximately 87.82% of the 
total land covers of the city. About 3003.48 hectares of the uncultivated lands that 
accounted for 70% of the total area have been changed into the Built-up surfaces 
270 
 
 
Figure 167. Also, 473.4 hectares of Uncultivated land and 288.36 hectares of the 
Waterbody have been transformed into the Built-up area. Would you mind taking a 
look at Figure 164 and comparing it to Figure 166? It helps to understand better the 
land covers transformation in terms of scale and types in this area. 
 
Figure 168 The map of changed land covers from 1972 to 2020 (by the author) 
Spatial analysis on the transformation of the land cover  
In general, the age of the current old texture of the Sari city back to the last century, 
and also some of them back to 250 years ago. The city was recognized as the capital 
of the Persian empire by Agha-Mohammad-Khan-e-Qajar13 in 1796. It has affected the 
physical body of the city. But after the foundation of the Pahlavi dynasty by Reza 
Shah in 1925, the city had been built up according to reformist and modernist ideas of 
the Reza Shah, which had been applied to all Iranian cities. And today, the modern 
zones of the city with a different landscape differ obviously from the old texture. Over 
decades, the city has experienced physical growth in different scales and directions 
                                              
13 He was king of Iran that time and the founder of the Qajar dynasty. 
271 
 
 
due to the different implemented strategies regarding governments' desires. For 
example, as mentioned above, political changes have played a significant role in 
changing and giving new functions to the city directly and indirectly. For example, 
this city is the capital of this metropolitan area and plays a tremendous position at the 
regional and national levels. Giving this city's new role to be a capital with 
administrational functions has also played considerable roles to be populated more 
than other cities in this metropolitan area. It had directly helped in the foundation of 
many central government organizations and offices and has provided valuable social-
economic opportunities for this city and thousands of new many jobs. As a result, the 
city became one of the interesting places for migrants from elsewhere at the regional 
and national levels.  
In general, the settling of people in the city follows the price of land parcels. Since 
the land value for around or outside the city's border is cheaper than the center or main 
body, it has provoked landowners to segregate agricultural lands informally and sold 
to the people for building new houses Figure 169.  
 
Figure 169, The radar graph of land values (by the author) 
 
272 
 
 
It should be noted, in Iran, according to the urban law "Article 100," the people are 
allowed to construct without a building permit and illegally, and finally, under cover 
of this role, they will be received a "Building permit." So this inappropriate legal 
article makes all urban plans affectless and powerless in the urban growth and 
formation process. In other words, under supports of this article, there is no matter 
how and where the people building and will be no paid attention to the city 
development plans, principles of urban design, and architectural factors. In such 
conditions, an urban planner can imagine how much dramatic the growth and 
development of a city can be in Iran. The city has been grown in sprawl form, and 
every day the people in the corners of this city start to construct a building illegally. 
Places with cheaper lands will be the most interesting locations to settle by the people. 
So this is one of the main factors that has been segregated the physical growth and 
borders of the city. The growth of the city in the north and northwest side is more 
segregated than the other sides. In the generated Cubic Trend map for the Vegetation 
to the Built-up area, the man illustrates many rings with different colors. In the map, 
the areas with the more intense change are indicated by the highest value of 0.30 and 
also colored with the strongest red Figure 170. The values between 0.30 up to 0.18 
show the zones with the highest intensity rate, and the values between 0.14 to -0.34 
show the area with sprawl growth and lowest intensity Figure 170.  
Roads are the other main factor that have progressed the continuation of sprawl 
growth. Because as mentioned above, most of the new residential areas and buildings 
have been constructed in the informal segregated agricultural lands and without basic 
urban infrastructures. And in such conditions, people for building tend to find some 
places with more accessibility to the other parts of the city and services, like the 
transportation system. After an interview with home builders, people, experts of the 
"Home, Road, and Urban Development Organization," and also three years of 
practical experience of the author in the "Commission Article 514" and working with 
                                              
14 The Comission Article 5 is a government organization and branch office of the 
ministry of Housing, Road and Urban Development in Iran.  Some main tasks of this 
comission are: controlling and analyzing urban development plans, apllying new 
273 
 
 
more than hundreds documentation, the results shows that accessibility to the road 
networks is one of the main criteria that determine the price of land parcels in this 
city. So, that's why in this city many people built up their homes near the main roads. 
In this city, there are six highways, and significantly the physical form of the city 
follows the location and direction of the roads; please take a look at Figure 171. 
 
Figure 170 The Cubic Trend map for the change of Vegetation to the Built-up area (by the author) 
As the above picture shows, the areas with the more intense change are indicated 
by the highest value of 0.30 and also colored with the strongest red. The values 
between 0.30 up to 0.18 show the zones with the highest intensity rate, and the values 
between 0.14 to -0.34 show the area with sprawl growth and lowest intensity. 
                                                                                                                                            
changes in the plans, dission-making for the all applications from applicants around 
changing type of land use, density of buildings, giving permit to the land segregations. 
274 
 
 
 
Figure 171 Illustration of the Built-up area, particularly roads (by the author) 
As the above picture shows, the city has six highways, and significantly the 
physical growth of the city follows the roads. 
 
Table 74: The projected land cover changes for the following decades 2030, 2040, and 2050 (by the author) 
2020 
Decades 2030 2040 2050 
 
Built up area 
3144.36 4154 4873 5548 
(Hectares) 
 (regarded as the start point) Predicted changes for each decade 
 
 
275 
 
 
 
Figure 172 The projected growth of the Built-up area in the following decades 2030, 2040, and 2050 (by the author) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
276 
 
 
The projected land use changes for the 2030s 
Table 75 Physical growth of the Built-up area for the projected decade 2030 (by the author) 
Category Hectares Legend 
Built-up  4154 BUILTUP 
 
 
 
Figure 173 Projected land use changes for the decade 2030 (by the author) 
 
 
 
 
 
 
277 
 
 
The projected Land use changes for the 2040s 
Table 76 Physical growth of the Built-up area for the projected decade 2040 (by the author) 
Category  Hectares  Legend  
Built-up  4873 BUILTUP 
 
 
Figure 174 Projected land-use changes for the decade 2040 (by the author) 
 
 
 
 
 
 
 
278 
 
 
The projected land use changes for the 2050s 
Table 77 Physical growth of the Built-up area for the projected decade 2050 (by the author) 
Category  Hectares  Legend  
  5548 BUILTUP 
 
 
Figure 175 Projected land use changes for the decade 2050 (by the author) 
 
For this case, this study mainly has focused on urbanization and sprawl growth. 
Accordingly, predictions of land-use changes primarily have concentrated on the 
urban physical growth that was defined here as the Built-up area. This study has 
projected forecasting the growth of the Built-up area for the three next decades, 
respectively 2030s, 2040s, and 2050s. The results of the LCM model have represented 
a significant sprawl growth that can happen in this city over the following decades. Of 
course, this study has made these predictions based on the LCM model and considered 
279 
 
 
the city's historical land-use changes to show how the city has been grown physically 
over the last half-century. 
The first prediction is projected for the 2030s, and the results show the continuation 
of dramatic land-use changes for this decade Figure 28. The Built-up area will be 
expanded to about 4154 hectares Table 75. Please consider, as shown by the results, 
the Built-up area of the city in the 2020s was 3144.36 hectares Figure 172. 
Unfortunately, the city will be faced with continuing the uncontrolled and 
unsustainable expansion of the built-up area to about 1010 hectares.  
The results of the second prediction for the 2040s have shown the continuation of 
non-sustainable physical growth Figure 174, and surprisingly an increase from 4154 
hectares to about 4873 hectares Table 76. It means the city in the 2040s will be 
experienced an explosion of physical sprawl growth for the built-up area in a total of 
about 1729 hectares for the following two decades. In other words, the model has 
predicted a grows about 893 hectares more than the built-up area indicated for the 
2030s Figure 172.  
The results of the third prediction for the 2050s have shown the continuation of this 
non-sustainable growth for the Built-up area Figure 175. The Built-up area will be 
expanded to about 5548 hectares; in other words, it is about 2403.64 hectares bigger 
than the area of the built-up sector in the 2020s Table 77. In the following, the study 
has provided more details to explain the main reasons for this non-sustainable growth 
and what forces are still the main drivers of this extreme land cover changes, 
particularly around and outside of the official borders of the city. 
280 
 
 
 
 
 
 
 
 
Chapter Eleven 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
281 
 
 
 
 
Land Use Changes around the 
Border of Sari City 
 
 
Urbanization and polarized development, unequal access to resources, facilities, 
and jobs, especially in small-sized cities and rural areas, has increased migration to 
this city. As a result, the city became bigger and bigger also more populated. For more 
information, please go to chapters eight and nine because these chapters discussed 
more about that and explained the main reasons specifically. In this chapter, objectives 
are concentrated exactly on the quantity and quality of land use changes and answer to 
the following questions. 
Is the city of Sari encounter with uncontrolled or remarkable land-use changes? 
If yes, why, how, and where happened these land-use changes?  
Where happened the most land use changes and why? 
What type of land-use changes happened inside or near the border and periphery 
areas of this city? 
What form of growth and development is facing this city considering the pattern of 
the land-use change? 
What type of land use changes happened mostly? Why and where? 
What type of land use changes happened minimally? Why and where? 
282 
 
 
 
Figure 176 The hybrid map of the geographical location of Sari city in the Mazandaran Metropol (by the author) 
As the above picture shows, the red polygon distinguishes Sari from other cities with yellow 
polygons. 
 
Figure 177 The hybrid map of the sphere of influence of Sari city at the local and regional levels (by the author) 
As the above picture shows, the yellow lines show the road network in the city's sphere of 
influence in the Sari district. The yellow polygons show the location of all cities in this metropolitan 
area, and the red line shows the political border of this Metropol. 
283 
 
 
 
Figure 178 The hybrid view over the studied area (by the author) 
 
Figure 179 The hybrid map of the physical growth of Sari between 1921-2006 (by the author) 
284 
 
 
The above picture shows the land changes between 1972-2020 that illustrated by the green, 
yellow, and red colors. 
 
Figure 180 The hybrid map of the physical growth of Sari city between 1972-2020 (by the author) 
As the above picture shows, the red color represents the subdivided lands that are still under 
construction: The yellow color illustrates the land parcels that were subdivided and built up. The 
green color indicates the land parcels that are subdivided but are not under construction. Around this 
city is covered by valuable green land covers. Unfortunately, because of sprawl growth and 
uncontrolled, thousands of hectares of farm lands that have been changed to the built-up area. And 
the map shows how the city grows in sprawl and scattered form. 
285 
 
 
 
Figure 181 The defined reference system for the created grid sheets (by the author) 
The above picture shows the defined grid reference system for creating the following land use 
maps between the numbers 0-75. Each grid has a particular number. A specific number is defined 
for each grid. The yellow lines show the proposed roads according to the last enacted 
Comprehensive Development Plan of Sari city. 
11.1. Some tips for reading and understanding the following maps: 
Please consider, this study has classified the study area into the three sectors to analyse better the 
land use changes as follow: 
1. The sector one covers the all land use changes that accured in the insight of the official 
border of Sari city,  
2. The sector two is a 1000 meters buffer that covers the all land use changes near the official 
border of this city. It includes two 500 meters buffer that covers the areas of the both sides of 
the official border. 
286 
 
 
3. The sector three is a 4000 meters buffer that covers all land use changes that occurred in the 
outside of the official border of the city.  
This is a rapid, uncontrolled, scattered, and sprawl urban physical growth that happened 
simultaneously around this city. And the city has been grown physically quite on the agricultural 
land. Please attention that if hear stressed particularly on the agricultural land is because, this city is 
surrounded by farmlands. It does not mean this study is limited just to the land-use changes that 
happened in farmlands. So, this study has provided a map with grids numbered from 0 to 75 to show 
the happened land-use changes in the 23 sheets. These sheets have covered the city's insight and 
outside of the official border of this city. Of course, you can see the happened land-use changes in 
the areas next to the numbered grids in each sheet. This thesis has consciously illustrated these land-
use changes by using satellite images to show how the green cover looks around this city? Are there 
geographical limitations that can hinder the physical expansion of this city? As you see, the city is 
located in a plain and flat area and surrounded by valuable agricultural lands. So, a satellite image 
with an aerial view helps better understand how this city devours these green covers uncontrolled 
and dramatically. Also, you have a direct and closed view over the change of the agricultural lands. 
All land-use changes are classified under three sectors as follows: 
1. Subdivided land parcels 
2. Subdivided and built-up area 
3. Subdivided and under construction 
11.2. The subdivided land parcels 
This sector includes all land-use changes that occured in all sectors of the studied area. These big 
agricultural lands have been divided into smaller parcels, regardless of legal or illegal.  
The polyline with pink color on the following maps is addressed to this sector.  
11.3. The subdivided and built-up parcels 
This sector includes all land-use changes that happened in all sectors of the studied area. The 
lands have been divided into smaller parcels and built up entirely, regardless of legal or illegal.  
287 
 
 
The polyline with yellow color  on the following maps is addressed to this sector. 
11.4. The subdivided and under construction parcels 
This sector includes all land-use changes that happened in all sectors the studied area. The lands 
have been divided into smaller parcels and are still under construction, regardless of legal or illegal.  
The polyline with red color on the following maps is addressed to this sector. 
 
 
Figure 182 The grid 0 from zone one and grid one from zone two (by the author) 
288 
 
 
 
Figure 183 The grids 6, 7, 8, 13, 14, and 15 from zone two (by the author) 
 
 
Figure 184 The grids 15, 23, 24, 25, and 26 from zone two (by the author) 
289 
 
 
 
Figure 185 The grids 27, 40, and 41 from zone two (by the author) 
 
 
Figure 186 The grids 38, 39, 40, 41, 52 and 53 from zone two (by the author) 
290 
 
 
 
Figure 187 The grids 37, 51, 52, and 53 from zone two (by the author) 
 
 
Figure 188 The grids 49, and 50 from zones one and two, and grids 51 and 61 from zone 2 (by the author) 
291 
 
 
 
Figure 189 The grids 60, 61, 63 nad 64 from zones three (by the author) 
 
 
Figure 190 The grid 67 from zones three (by the author) 
292 
 
 
 
Figure 191 The grid 70 from zones three (by the author) 
 
 
Figure 192 The grid 73 from zones three (by the author) 
293 
 
 
 
Figure 193 The grid 75 from zones three (by the author) 
 
 
Figure 194 The grid 72 from zones three (by the author) 
294 
 
 
 
Figure 195 The grids 68 and 69from zones three (by the author) 
 
 
Figure 196 The 66 and 65 from zones three (by the author) 
295 
 
 
 
Figure 197 The grids 56, 57, 58, 59 and 62 from zones three (by the author) 
 
 
Figure 198 The grids 54, 55, and 56 from zones three (by the author) 
296 
 
 
 
Figure 199 The grids 54, 55, and 56 from zonesone and  three, and grids 28, 29, 30, 42, 43, and 44 from the zone one (by the author) 
 
 
Figure 200 The grid 28 from zone one (by the author) 
297 
 
 
 
Figure 201 The grids 54, 55, and 56 from zones three 16, 17, 28, 29,and 30 from zone one (by the author) 
 
 
Figure 202 The grids 2, 3, 9, and 56 from zones one (by the author) 
298 
 
 
 
Figure 203 The grids 0, 2, 3, and 4 from zones one (by the author) 
 
 
Figure 204 The grid 0 from zone one and two, and grid 1 from zone two (by the author) 
299 
 
 
 
Figure 205 The land use map Sari city. The map provided by author, and the data from (The Ministry of Housing, Road, and Urban 
Development, 2015) 
300 
 
 
11.5. The interactions among the factors including: time 
of development, urban density and area of land parcels 
The effects of the urban density on the land consumption and subdivision 
Given this thesis, in general, some zones of this city that have experienced erlier 
city building than younger quarters, on the one hand, have a higer rate of density, on 
the other hand the area of land parcels are smaller than younger quarters. Because, the 
factor land value plays a significant role. Where the land value is high, area of land 
prcels has reduced. It is an strategy that make the land parcels payable for more people 
Figure 207. According to the Figure 206, the area A that addressed to the Inner-zone, 
has the higest rate population and buildings densities. This area generally has the 
erliest constructed buildings. And this sector has the higest rate of land value, 
subdivided land parcels are smaller, but has more high-rise buildings. In other words, 
insteade growth horizentally, tried to reduce area of percels and growth vertically 
Figure 218. It has increased more concentration of building and population in this 
sector.  
 
Figure 206 Urban density and its effect on the size of land when subdividing (by the author) 
 
Considering the Figure 206, the area B addressed to the buffer 1000 meters. This 
area is closed to the city and has the newest tissues, buildings and scattered. And land 
value in this sector is lower than sector A, but the area of subdivided land parcels are 
301 
 
 
significantly biger than sector A. Zone B has fewer high-rise buildings and more low-
rised buildings. In other words, insteade growth vertically, tried to increase area of 
percels and growth horizentally. It has decreased concentration of building and 
population in this sector. 
And the area C addressed to the buffer 4000 meters. This area refers to periphery 
area included suburbs and rural around this city. Land value in this sector is lower 
than sectors A and B, but the area of subdivided land parcels are significantly biger 
than sectors A and B. The most built up buildings in zone C are low-rised, area of 
percels are bigger than other sectors and has the lowest concentration of building and 
population. 
 
 
Figure 207 The map of land values combined with the changed land parcels (by the author) 
 
302 
 
 
11.6. Planned and unplanned land subdividing and 
zoning 
Plan-based zoning and land subdividing help to use land resources efficiently and 
effectively. It provides frameworks on the form and scale of buildings and parcels to 
define the character of a neighborhood or quarters considering sustainability 
principles. Also, it provides a common understanding of allowable land uses for 
projects considering the community’s articulated vision. Plan-based zoning 
encourages mixed-use development to manage better consumption of urban lands, 
minimize waste of valuable urban lands when land subdividing and allocating space or 
lands for streets or buildings, and helps to have productive and livable urban spaces. 
 In a plan- and form-based zoning, increasing the efficiency of land consumptions 
and maximum use of the capacity of urban spaces is one of the main goals. But in 
unplanned and uncontrolled zoning, land subdividing and using spaces is not efficient. 
Also, concerning principles of urban landscapes and harmony between elements, there 
are many contrasts between form, wide and capacity of streets, building, density, and 
land parcels. Also, in this area, no one paid attention to the accessibility and 
compatibility factors.  
In this regard, this study has provided two examples from different places in the 
city of Sari. The first one (see Figure 208) shows plan-based zoning located in the 
inner-zone, zone 1. And in this area, planners have tried to realize harmony between 
places, parcels, and buildings considering the factors compatibility and accessibility. 
But in contrast, the second one (see Figure 209) shows a place that is located in the 
urban edge, zone 3, buffer 1000 meters. In this sample case, landowners have tried to 
subdivide farmlands without a permit and consider zoning principles. Also, irregular 
street system, inattention to factors compatibility and accessibility, inattention to 
density and size of land parcels, inattention to the high of buildings, architectural 
factors, materials, and facades of the building are the salient features of these areas. 
This is a sample of sprawl and uncontrolled zoning and land subdividing that are 
happening daily around this city, especially in the buffer 1000 meters. 
303 
 
 
 
 
Figure 208 Tabarestan is a mix-use development project horizontally integrating multifamily housing and retail, clinics, 
and other public services. This area is located in zone one of the city Sari (by the author) 
 
 
Figure 209, An exemplar uncontrolled and sprawl area that is located in zone three, in the buffer 1000 meters, with 
growing single-use buildings projects on land parcels without accessibility to the basic services. These building projects 
started by private investors without getting building permits (by the author) 
 
304 
 
 
Sprawl Growth, land consumption, and land subdivision in Sari City 
Zone 1 
This zone encompasses half of the north and west sides and the northwest part of 
this city Figure 181.   
Subdivided lands 
This zone encompasses half of the north side, northwest, and the half of west of the 
part of this city.  The layer of the Subdivided lands is the first group of these three 
classifications that were introduced above Figure 211. In zone one, in terms of area, 
the largest land subdivisions happened in the buffer 4000 meters, about 75403.39 m2. 
They were recently subdivided and still are not under the building (see Figure 210). 
 
Figure 210 This big orchard is destroyed for starting a building project and and subdivided into many parcels (by the 
author) 
 
As shown in Figure 210, just in one case, people have changed a big orchard about 
46000 m2 to a new residential area. The above satellite image, left up, illustrated this 
305 
 
 
orchard in 2010. And in left down, the orchard is completely destroyed. In the center 
of Figure 210 illustrates that this farmland is subdivided into small land parcels to 
build new buildings for constructing a new residential area.  
As shown in Table 78, most land-use changes happened in the buffer 4000 meters, 
then in the buffer 1000 meters, and the lowest in the inner zone. And the reasons are 
that the subdivided lands in the periphery area were agricultural parcels. 
For this sector, about 51% of the changes happened in the buffer 4000 meters, 40% 
in the buffer 1000 meters, and 9% in the Inner-zone Figure 212. 
 
 
Figure 211 The subdivided land parcels in zone one considering the three classes of buffers (by the author) 
 
306 
 
 
 
Figure 212 The percent of the subdivided land parcels in zone one considering the three classes of buffers (by the 
author) 
 
Table 78 The area of the subdivided land parcels in zone one considering the three classes of buffers (by the author) 
Zone's Class Classes Count Square Meters 
Zone1 Subdivided lands- Inner-zone 2 13204.85404 
Zone1 Subdivided lands- buffer_1000_meters 6 59019.49445 
Zone1 Subdividedlands- buffer_4000_meters 3 75403.39321 
Sum 11 147627.7417 
 
 
The subdivided lands and under construction 
The sub-divided lands and under the construction layer are the second group of 
these three classifications Figure 213. In zone one, in terms of area, the largest land 
subdivisions happened in the buffer 1000 meters, about 1873760.177 m2.  
As shown in Table 79, the most land use changes happened in the buffer 1000 
meters, because this area refer to the urban edges where are in growing process and 
most of new buildings are building in in these sectors. And the buffer 4000 meters has 
the second place then in and the lowest changes have taken place in the Inner-zone.  
For this sector, about 79% of the changes happened in the buffer 1000 meters, 15% 
in the buffer 4000 meters, and 6% in the Inner-zone Figure 214. 
307 
 
 
 
Figure 213 The subdivided and under construction land parcels in zone one considering the three classes of buffers (by 
the author) 
 
Figure 214 The percent of the subdivided and under construction land parcels in zone one (by the author) 
 
Table 79 The area of the subdivided and under construction land parcels in zone one considering the three classes of 
buffers (by the author) 
Zone's Class Classes Count Square Meters 
Zone1 Subdivided_lands_and_under_construction-Between_Inner-zone 5 138838.2012 
Zone1 Subdivided_lands_and_under_construction-_buffer_1000_meters 36 1873760.177 
Zone1 Subdivided_lands_and_under_construction _buffer_4000_meters 15 355767.8339 
Sum 56 2368366.212 
 
308 
 
 
The subdivided lands and Built-up  
The layer of the Subdivided lands and Built-up is the third group of these three 
classifications Figure 215. In zone one, in terms of area, the largest land subdivisions 
happened in the buffer 4000 meters, about 53700.40 m2.  
As shown in Table 80, most land use changes happened in the buffer 4000 meters. 
That was happened in the periphery of this city, in a village quite near the city. These 
villages are growing and populating because the dwellers tend to work in the city but 
live outside of the city, away from the daily traffic and sound pollutions. And the 
buffer 4000 meters has the second place then in, and the lowest changes have taken 
place in the Inner-zone.  
For this sector, about 59% of the changes happened in the buffer 4000 meters, 38% 
in the buffer 1000 meters, and 3% in the Inner-zone Figure 216. 
 
 
Figure 215 The subdivided and build up land parcels in zone one considering the three classes of buffers (by the author) 
 
309 
 
 
 
Figure 216 The percent of the subdivided and build up land parcels in zone one considering the three classes of 
buffers (by the author) 
 
Table 80 The area of the subdivided and build up land parcels in zone one considering the three classes of buffers (by the 
author) 
 Classes Count Square Meters 
Zone's Class 
Zone1 Subdivided_lands-and_built_up-Between_Inner-zone 1 2945.105654 
Zone1 Subdivided_lands-and_built_up _buffer_1000_meters 2 34139.82511 
Zone1 Subdivided_lands-and_built_up _buffer_4000_meters 1 53700.40225 
Sum  4 90785.33301 
 
 
 
 
 
 
 
 
310 
 
 
Zone 2 
This zone encompasses half of the north and east sides and the northeast part of this 
city Figure 181. 
The subdivided lands 
The layer of the Subdivided lands is the first group of these three classifications 
Figure 221. In zone two, in terms of area, the largest land subdivisions happened in 
the buffer 1000 meters, about 633828.44 m2. But revers, in zone one, the largest land 
subdivisions happened in the buffer 4000 meters. For zone two, one of the main 
reasons refers to the natural restriction. In this part of the city located the Tajan river, 
and the river has limited physical expansion of the city compared to the other zones 
(see Figure 217, Figure 218, Figure 219, and Figure 220).  
 
 
Figure 217 The geographical position of the Tajan river considering the official border to the Sari city (by the author) 
311 
 
 
 
Figure 218 The presentation of the density of big buildings in the inner zone of Sari city (by the author) 
As presented in the above picture, the red color distinguishes the shapes of the big 
buildings between 5-8 floors from small buildings and land parcels that are colored 
white. The purple color shows the official border, and the blue represents the Tajan 
river. 
 
Figure 219 The geographical position of the Tajan river considering the physical body of Sari city (by the author) 
312 
 
 
 
Figure 220 The road networks of Sari city (by the author) 
 
The other factor refers to the land value and development policies in zone one. As 
shown in Figure 207, just two sectors have the highest land value, one of them located 
in this zone. It has affected the agricultural lands near these sectors because people 
have tried to subdivide valuable agricultural lands and construct new buildings for 
more profit. 
As shown in Table 81, most land use changes happened in the buffer 1000 meters. 
That was happened in the periphery of this city, in a village quite near the city. These 
villages are growing and populating because the dwellers tend to work in the city but 
live outside of the city, away from the daily traffic and sound pollutions of big cities. 
And the buffer 4000 meters has the second place then in, and the lowest changes have 
taken place in the Inner-zone.  
For this sector, about 83% of the changes happened in the buffer 1000 meters, 13% 
in the buffer 4000 meters, and 4% in the Inner-zone Figure 222. 
 
313 
 
 
 
Figure 221 The subdivided land parcels in zone two considering the three classes of buffers (by the author) 
 
Figure 222 The percent of the subdivided land parcels in zone two (by the author) 
Table 81 The area of the subdivided land parcels in zone two considering the three classes of buffers (by the author) 
Zone’s Class Classes Count Square Meters 
Zone2 Subdividedlands-Between Inner-zone  5 31556.23449 
Zone2 Subdividedlands _buffer_1000_meters 24 633828.4419 
Zone2 Subdividedlands _buffer_4000_meters 4 97743.76954 
Sum  33 763128.4459 
314 
 
 
The subdivided lands and under construction 
The layer of the Subdivided lands and under Construction is the second group of 
these three classifications Figure 223. In zone two, in terms of area, the largest land 
subdivisions happened in the buffer 1000 meters, about 1145001.11m2.  
As shown in Table 82, most land use changes happened in the buffer 1000 meters. 
One of the main reasons refers to the villages that are closed to this area. The city has 
been expanded physically towards the villages that one day had a considerable 
distance from the city as far as, in some areas, they are going to link together. Also, 
this area is urban edges where the most and highest building activities have been 
taking place every day. And the buffer 4000 meters has second place, and the lowest 
changes have taken place in the Inner-zone.  
For this sector, about 82% of the changes happened in the buffer 1000 meters, 15% 
in the buffer 4000 meters, and 3% in the Inner-zone Figure 224. 
 
 
Figure 223 The subdivided and under construction land parcels in zone two considering the three classes of buffers 
(by the author) 
 
315 
 
 
 
Figure 224 The percent of the subdivided and under construction land parcels in zone two (by the author) 
Table 82 The area subdivided and under construction land parcels in zone two (by the author) 
Zone's Class Classes Count Square Meters 
Zone2 Subdivided_lands_and_under_construction-Between_Inner-zone 3 42657.35672 
Zone2 Subdivided_lands_and_under_construction _buffer_1000_meters 22 1145001.117 
Zone2 Subdivided_lands_and_under_construction _buffer_4000_meters 6 206010.454 
Sum  31 1393668.927 
The subdivided lands and Built-up  
The layer of the Subdivided lands and Built-up is the third group of these three 
classifications Figure 225. In zone two, in terms of area, the largest land subdivisions 
happened in the buffer 1000 meters, about 226054.86 m2. Interestingly, despite the 
low number of the land parcels that have changed in the buffer 4000 meters, that were 
three parcels, but the area is remarkably large. The reason refers to the construction of 
a big Water treatment center for this city in this area. About 10 Hectares of valuable 
agricultural lands were used for building this center. The other reason refers to the 
road networks development policies in this city. As shown in Figure 179, the city has 
designed proposed roads, especially for this area, to provide a possibility to allow the 
city to continue physical growth and expansion in this area. 
As shown in Table 83, considering the area of land use changes, the buffer 1000 
meters has faced the largest changes. And the buffer 4000 meters has second place, 
and the lowest changes have taken place in the Inner-zone. 
316 
 
 
For this sector, about 55% of the changes happened in the buffer 1000 meters, 41% 
in the buffer 4000 meters, and 4% in the Inner-zone Figure 226. 
 
Figure 225 The subdivided and built-up land parcels in zone two considering the three classes of buffers (by the author) 
 
Figure 226 The percent of the subdivided and built-up land parcels in zone two (by the author) 
 
Table 83 The area of the subdivided and built-up land parcels in zone two considering the three classes of buffers (by the 
author) 
Zone's Class Classes Count Square Meters 
Zone2 Subdivided_lands-and_built_up-Between_Inner-zone 1 16462.1257 
Zone2 Subdivided_lands-and_built_up _buffer_1000_meters 18 226054.8572 
Zone2 Subdivided_lands-and_built_up _buffer_4000_meters 3 169104.6135 
Sum  22 411621.5963 
317 
 
 
Zone 3 
This zone encompasses half of both west and east sides, south, southwest, and 
southeast part of this city Figure 181. 
The subdivided lands 
The layer of the class of the Subdivided land is the first group of these three 
classifications Figure 230. In zone three, in terms of area, the largest land subdivisions 
happened in the buffer 1000 meters, about 146197m2. The subdivided land 
significantly follows the road networks, especially the proposal roads network Figure 
229. But as shown in the figures between 6-29, the proposal roads pass through the 
agricultural lands. But it should be noted that the city under this strategy has attached 
about 4,393 Hectares of agricultural lands and villages to the city Figure 227 and 
Figure 228.  
On the one hand, it provides new opportunities and a big market for home building 
companies and persons, and on the other hand, it increases consumption of valuable 
agricultural lands and allows the city to grow horizontally, sprawl and non-
sustainable. The continuation of a growth that has no public profit and just secure 
profits of private sectors. It is just ruining the environment and natural resources. 
Additionally, physical expansion increases service costs for constructing gas, water, 
electricity, and swear networks. Also, it increases the use of private cars, resulting in 
an increase in the consumption of fossil fuels and consequently increases greenhouse 
gas emissions. In other words, it intensifies climate crisis, global warming, and the 
earth's vulnerability.  
318 
 
 
 
Figure 227 The peripheral areas attached to the physical body of Sari city (by the author) 
The above picture presents the periphery areas of Sari city, including villages and 
agricultural lands attached to the physical body of the city according to the last 
development plan. The total area of the colored sectors from one to six is about 4,393 
Hectares. 
 
Figure 228 The proposed roads network of Sari city (by the author) 
The above picture presents the proposed roads network according to the last 
development plan of Sari city, which attached many agricultural lands and villages to 
the physical body of the city. 
319 
 
 
 
Figure 229 The layers of the physical body of Sari city (by the author) 
As presented in the above picture, the first layer from the top is the layer of land 
use, the second is the layer of the current road networks, and the last is the layer of the 
proposed road networks. 
As shown in Table 84, most land use changes happened in the buffer 1000 meters. 
And the buffer 4000 meters has the second place then in, and the lowest changes have 
taken place in the Inner-zone.  
Table 84 The area of the subdivided land parcels in zone three considering the three classes of buffers (by the author) 
Zone's Class Classes Count Square Meters 
Zone3 Subdividedlands-Between_Inner-zone 3 22034.09492 
Zone3 Subdividedlands _buffer_1000_meters 8 146197.0115 
Zone3 Subdividedlands _buffer_4000_meters 2 43181.75575 
Sum 13 211412.8622 
 
 
For this sector, about 69% of the changes happened in the buffer 1000 meters, 21% 
in the buffer 4000 meters, and 10% in the Inner-zone Figure 231. 
320 
 
 
 
Figure 230 The subdivided land pa rcels in zone three considering the three classes of buffers (by the author) 
 
 
Figure 231 The percent of the subdivided land parcels in zone three (by the author) 
 
The subdivided lands and under construction 
The layer of the Subdivided lands and under Construction is the second group of 
these three classifications Figure 232. In zone three, in terms of area, the largest land 
subdivisions happened in the buffer 1000 meters, about 2686552.23 m2. The results of 
these sectors signify the results of the last sector, Subdivided lands. At the same time, 
321 
 
 
locals, landowners, and home building companies are subdividing farmlands and 
constructing new buildings in this sector. Most of the farmland change cases of this 
group happened in this buffer, and one of the main reasons refers to the land value. As 
shown in the map of land value Figure 207, this zone has the lowest land value, and 
most of the low-income families or between low and middle class trying to settle in 
this area. This is one of the main reasons that more farmland has changed in this zone. 
As shown in Table 85, most land use changes happened in the buffer 1000 meters 
because this area refers to the urban edges where are under growing process, and most 
of the new buildings are building in these sectors. And the buffer 4000 meters has the 
second place, and the lowest changes happened in the Inner-zone.  
For this sector, about 62% of the changes happened in the buffer 1000 meters, 31% 
in the buffer 4000 meters, and 7% in the Inner-zone Figure 233. 
 
Figure 232 The subdivided and under construction land parcels in zone three considering the three classes of buffers (by 
the author) 
322 
 
 
 
Figure 233 The percent of the subdivided and under construction land parcels in zone three (by the author) 
Table 85 The area of the subdivided and under construction in zone three considering the three classes of buffers (by the 
author) 
Zone's Class Classes Count Square Meters 
Zone3 Subdivided_lands_and_under_construction-Between_Inner-zone 4 314717.8734 
Zone3 Subdivided_lands_and_under_construction-Between_buffer_500_meters 46 2686552.23 
Zone3 Subdivided_lands_and_under_construction- 18 1339382.264 
Between_buffer_4000_meters 
Sum  68 4340652.368 
 
The subdivided lands and Built-up  
The layer of the Subdivided lands and Built-up is the third group of these three 
classifications Figure 234. In zone three, in terms of area, the largest land subdivisions 
happened in the buffer 1000 meters, about 457797.28m2. One of the main reasons 
refers to land value as explained before, and the other refers to joining near villages to 
the city. Zone three has the longest border to the villages and suburbs. This is a big 
market for the farmers and the easiest way to get money more than all revenues during 
20 or 30 years farming on their farmlands.  
Also, locating the Shahrak-e-Farhangian as one of the biggest suburbs of this city in 
this area, a place is still under development and building, effects on the land market 
323 
 
 
and land values in this zone remarkably, which motivates other farmers to subdivide 
and sell their lands. 
As shown in Table 86, considering the area of land use changes, the buffer 1000 
meters has been faced the largest changes. And the buffer 4000 meters has the second 
place and the lowest changes have taken place in the Inner-zone.  
For this sector, about 88% of the changes happened in the buffer 1000 meters, 10% 
in the buffer 4000 meters, and 2% in the Inner-zone Figure 235. 
 
Figure 234 The subdivided and built-up land parcels in zone three considering the three classes of buffers (by the author) 
324 
 
 
  
Figure 235 The percent of the subdivided and built-up land parcels in zone three (by the author) 
 
Table 86 The area of the subdivided and built-up land parcels in zone three considering the three classes of buffers (by 
the author) 
Zone's Class Classes Count Square Meters 
Zone3 Subdivided_lands-and_built_up-Between_Inner-zone 1 10287.79314 
Zone3 Subdivided_lands-and_built_up _buffer_1000_meters 6 52760.88514 
Zone3 Subdivided_lands-and_built_up _buffer_4000_meters 1 457797.2822 
Sum 8 520845.9605 
 
 
 
 
 
 
 
 
 
 
325 
 
 
Overall view of the three Zones concerning the classified layers 
The subdivided lands 
Providing a comprehensive view of all three zones and the subdivided and changed 
lands helps to know how the land-use changes and subdivisions are in the three zones. 
According to the results, most of the layer Subdivided lands happened in zone two 
Figure 236. It recognizes that here is the area that has big opportunities for home 
builders. For zone two, as shown in the map of land value, the land value in the area 
on the other side of the Tajan river is low Figure 207. And as explained before, in this 
city, the land value plays a significant role in the land use change and subdivision. It 
also shows the general trend of the land market that currently is concentrated in this 
area and will be a massive building field in the following month or years. If you see 
Table 88, there is a significant difference between the total area of the subdivided land 
among the three zones. About 68,01 % of the land subdivisions happened in this zone, 
76.31 Hectares. About 21,14 hectares 18,84% of the land subdivisions in zone three, 
and about 14,76 hectares (13,15%) in zone one. 
 
 
Figure 236 The area of the subdivided land parcels considering the three zones  (by the author) 
 
 
326 
 
 
Table 87 The area of the subdivided land parcels considering the three zones (by the author) 
Zone's Class Classes Count Square Meters Hectares 
Zone 1 Subdivided lands 11 147.628 14,76 
Zone 2 Subdivided lands 33 763.128 76,31 
Zone 3 Subdivided lands 13 211.413 21,14 
Sum  57 1.122.169 112,22 
 
The subdivided lands and under construction 
According to the results, most of the subdivided farmlands and still under 
construction have been taken in zone one Figure 237. As showed in Table 88, about 
236,84 Hectares (46,43%) of changes happened in this zone. It means here is the 
developing zone, and most building projects have been taken place here.  
Also, there is no considerable difference for zones two and three, and 139,37 
Hectares (27,32%) of land use changes happened in zone two, and 133,94 Hectares 
(26,26%) land use changes happened in zone three. 
 
 
Figure 237 The area of the subdivided and under construction land parcels considering the three zones (by the author) 
 
 
327 
 
 
Table 88 The area of the subdivided and under construction land parcels considering the three zones (by the author) 
Zone's Class Classes Count Square Meters Hectares 
Zone 1 Subdivided_lands_and_under_construction 56 2.368.366 236,84 
Zone 2 Subdivided_lands_and_under_construction 31 1.393.669 139,37 
Zone 3 Subdivided_lands_and_under_construction 18 1.339.382 133,94 
Sum  105 5.101.417 510,14 
The subdivided lands and Built-up  
According to the results, most of the subdivided and built-up farmlands have been 
taken in zone three Figure 238. As showed in Table 90, about 52,08 Hectares 
(50,90%) of changes happened in this zone. Because here is the area that the process 
of building will finish faster than other zones. As explained before, most of between 
low and middle classes living here. These groups normally try to have a roof over 
their head, so most of the buildings are small and have one or two floors. Therefore, 
these small projects are completed faster than big building projects in the other zones. 
For example, in the zone because of high land value Figure 207, home builders try to 
increase the height of buildings with more floors to get more profits. 
Also, in zone two, about 41,16 Hectares (40,23%) of land use changes happened in 
zone two, and 09,08 Hectares (8,87%) of land use changes happened in zone three. 
 
Figure 238 The area of the subdivided and built-up land parcels considering the three zones (by the author) 
328 
 
 
 
Table 89 The area of the subdivided and built-up land parcels considering the three zones (by the author) 
Zone's Class Classes Count Square Meters Hectares 
Zone 1 Subdivided_lands-and_built_up 4 90.785 9,08 
 Subdivided_lands-and_built_up 22 
411.622 41,16 
Zone 2 
Zone 3 Subdivided_lands-and_built_up 8 520.846 52,08 
Sum  34 1.023.253 102,33 
 
An general view over the changes of the three zones considering the classes 
Given the results of this study, in general, most land use changes happened in zone 
three. About 507,29 hectares of farmland that have been changed in this city occurred 
in this zone. In other words, about 50% of land use changes occurred here. And 
between zone two and one, there is no considerable difference. In zone one in total, 
about 260,67 Hectares of agricultural lands have changed, and in zone two, about 
256,84 Hectares (Table 91). 
 
Figure 239 The summed area of the changed land uses considering the three classes (by the author) 
 
 
329 
 
 
Table 90 The summed area of the changed land uses considering the three classes (by the author) 
Zones Classes Count Hectares 
Subdivided lands 
Zone 1 Subdivided_lands_and_under_construction 71 260.6779 
Subdivided_lands-and_built_up 
Subdivided lands 
Zone 2 Subdivided_lands_and_under_construction 86 256.8419 
Subdivided_lands-and_built_up 
Subdivided lands 
Zone 3 Subdivided_lands_and_under_construction 89 507.2911 
Subdivided_lands-and_built_up 
Sum 246 1024.811 
 
330 
 
 
 
 
 
 
 
 
Chapter Twelve 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
331 
 
 
 
 
 
 
 
 
Conclusions and Solutions 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
332 
 
 
12.1. Conclusions  
“Intensifying uncontrolled land-use changes” 
Based on this study's results, unfortunately, Iran's planning system has no integrity 
with the political structure and social system, and there is no coordination and 
agreement among the players, including enactors, executors, authorities, and planners. 
The conflict between the political structure and the planning system has failed 
development plans, and these plans were not executed successfully. Also, this issue 
has increased inequality because of the unequal distribution of resources and 
opportunities between urban and rural areas. For example, since the last six decades, 
the Comprehensive and Detailed Plans have been employed as the main urban 
development plans in Iran. But according to the results, the nature of these plans 
contrasts the nature of Iran’s political and administrative systems structurally and 
functionally! Therefore, these plans became passive, and neither couldn’t reach their 
specified goals and have created the following issues: 
 massive urban-rural migration 
 urban areas, particularly big cities such as Sari became bigger and 
overpopulated, and resources, services, and capacities are at the limit. 
 unequal distribution of resources and infrastructures among the city zones. 
 unequal access to the social and health services between the city zones. 
 unequal distribution of urban per capita  
The other issue is centralization. After the revolution in 1979 occurred many 
unwelcome changes in the government's functions. As a result, Iran’s political and 
administrative systems became centralized. Accordingly, this issue has imbalanced the 
national power, created structural problems and disintegrated the planning, political, 
and public sectors from each other structurally and functionally. Centralization has 
increased the power of radical Islamists in politics and limited the presence of the 
majority in the policy- and strategy-making process. The presence of these people in 
the development policies and strategies making caused incoordination and 
disagreement among the actors, including authorities, planners, and people. Dictating 
333 
 
 
decisions and orders by the national organizations to the locals and ignoring theirs's 
opinions have decreased public participation in the planning and execution steps and 
minimized using local potential in the developing process.  
The next issue refers to the ambiguities and weaknesses in enacted legislations and 
laws, which have negatively affected social-economic orders and activities. For 
example, the Law of Article 100. This law allows people to construct buildings on a 
land parcel without permits. Also “The Height of Buildings Act” is the other issue that 
has intensified land-use changes. Because of this act, high-raised building is not 
allowed in this metropolitan area and also in Sari. This issue has increased the need 
for new raw land parcels to construct new buildings.  
“The pattern of urban development in the Mazandaran metropolitan area, and 
distribution of the population” 
According to the models' results, Iran's urban population growth will continue in 
the following decades. Unfortunately, the most significant part of the growth of Iran's 
urban population and also the Mazandaran metropolitan area resulted from the 
migration of people from rural to urban areas. And this issue has imbalanced the urban 
hierarchies of this metropolitan area. And today, we are witnessing a polarized growth 
in this region, which resulted from the unequal distribution of development 
opportunities, infrastructures, and facilities between big cities.   
Also, the imbalance between the population size of the first big city (Sari) and the 
smallest city (Gazanak) is too much. Sari has about 347402 population, and Gazanak 
has about 319 people. Also it should be noted that, the population of Sari is more than 
the population of 42 cities under 25000, which is about 321,242 people. 
Also, according to the regression model results, a strong inverse correlation exists 
between the rank and size of a cities. Dispersion of logarithm in the cities with a 
population between 50000-500000 is more imbalanced than the cities under 50000. 
Among the 60 cities of this metropolitan area, about 31 percent of the urban 
population has concentrated just in two big cities, and 71 percent of the urban 
population lives in the rest 58 cities. In other words, 31 percent of the urban 
334 
 
 
population has concentrated just 3.3 percent of the total cities, and 71 percent of the 
population in 96,67 percent of the total cities.  
Between the years 2006-2016 happened a little growth in the population of 
medium-sized cities in this metropolitan area. If it continues, it helps to decrease the 
migration of people to the big cities and directs the surplus of the population between 
the medium-sized cities. Providing more facilities for the both medium- and small-
sized cities motivates people to stay in these cities and helps to decrease the 
concentration of population in the big cities. 
Sari has been faced remarkable population growth since the last decades. And the 
projected demographic models have shown that, this growth will continue for the 
following decades because of continuing the urban-rural migration. But, the 
continuation of the population growth is equal to the physical growth of Sari. As 
shown in Figure 240, the development and physical growth of Sari has followed 
significantly the main five express roads. Concerning the simulated simple dynamic 
model in Figure 240, the physical form of Sari looks like an octopus with long arms. 
For Sari there is a significant interaction between the network development also land 
use changes over time. And this interaction has progressed a massive physical growth, 
which happened first along the express roads and later along the arterial streets.  
335 
 
 
 
Figure 240 The map of the physical growth of Sari city (by the author) 
The map shows the growth of the city from 1921 to 2020. It also illustrated the last 
land cover changes around the city in the decade 2020. Also, the direction nodes show 
in which direction is going the city's growth considering road connections. 
The results of remote sensing have shown that, sari has grown uncontrolled and 
scattered, and such non-sustainable land-use changes have faced Sari with many 
issues. The city physically became seven times bigger than in the year 1972. About 
85% growth of the city happened between 1972-2020. In 1972 the area of the city was 
about 757.08 hectares, but in 2020, the area expanded dramatically to about 5013.37 
hectares. 
In other words, about 4.256 hectares of valuable farmlands have changed into urban 
areas during the last five decades. The Built-up area became ten times bigger than in 
the year 1972. Which was in the year 1972 was about 338.96 hectares, but in 2020, 
has expanded dramatically to about 3144.36 hectares. And it should be noted that, 
about 90% of the growth of the built-up area has happened during the last five 
decades! 
336 
 
 
According to the results of the aerial images analyzed by ArcGIS, most of the 
uncontrolled land use changes happened near the official border (buffer 1000 meters) 
and in the peripheral area (buffer 4000 meters). About 68,01 % of the subdivided land 
parcels happened in zone two, about 18,84% of in zone three, and about 13,15% in 
zone one. So, most of the subdivided lands are identified in zone two. Because for this 
city, land value plays a significant role in land-use change and subdivision, and the 
land value for the area located on the right side of the Tajan river is remarkably low. 
Concerning the current situation and the mentioned factors, this thesis predicts 
massive building projects in zone two in the following month or years! 
According to the results of the projected land use changes, the Built-up area will 
increase as follow: 
 about 4154 hectares up to 2030 (about 24.31% growth) 
 about 4873 hectares up to 2040 (about 35.48% growth) 
 about 5548 hectares up to 2050 (about 46.66% growth) 
“Development, economic forces and the intensification of land use changes and 
consumptions” 
Iran, particularly since 2012, has been facing many extreme economic problems. 
But, as far as the government has access to enormous oil resources and can easily earn 
millions of dollars, they will not be motivated to care about the other economic 
sectors. And this issue has affected the urban markets directly and indirectly. Because 
the enormous wealth of oil resources has increased the centralization of power and 
wealth in the public agencies. Oil revenue has gradually expanded the government's 
role in all parts of daily life, and today, the government can nationwide control market 
forces and players. As a result, today's government became the main and absolute 
employer of the market. And when the job market like today is unstable and millions 
of people are jobless, so the people have no chance out of working for the 
government. In such a condition, the government is gives the job to whoever is with 
the government and not against it! So, it increases the power of the government in the 
society. Therefore, today's government does not need more the surplus of rural goods 
337 
 
 
and the flow of wealth and capital from rural to the cities. Billions of revenue from 
selling under-earth oil have changed the flow of wealth and capital from rural toward 
the cities. And through commercializing urban capitals and consolidating the 
government’s position as an the main employer in the cities, they have restricted rural 
development and pushed the villagers towards cities to find a job. 
At the national level, Sari city has played a considerable role in providing 
agricultural goods also services, and industrial activities in the second and third 
places. However, in the Mazandaran metropolitan area, Sari city has a dominant role 
in the service activities, especially in areas under the direct sphere of influence of this 
city. So, this fact clears that, Sari as a capital city, has the most service centers, 
financial centers, administrations, health and education centers, and recreational 
activities. According to the results, the following factors have played substantial roles 
in developing Sari at the local, regional, and even national levels: historical 
background, geographical location, environmental potentials, administrative functions, 
and being the capital of the Mazandaran metropolitan area.  
On the one hand, these above functions have provided many economic 
opportunities for Sari city and have developed Sari’s role in the region. On the other 
hand, the unequal distribution of resources, facilities, capital, and job opportunities in 
this metropolitan area have faced Sari city with the following problems. For example, 
in the last decades, thousands of people have been migrated to this city to find new 
jobs, and today this city is overpopulated. So, today’s capacities and infrastructures of 
the city cannot meet the needs of dwellers. Sectoral growth and prioritizing one place 
over other places have expanded suburbs and sprawl growth, which forced people, 
especially low-income families, to find cheaper land parcels without any basic service 
near the official borders, urban fringe, or hinterland. 
Also, constructing new road networks has changed the valuable farmlands. These 
new roads have grown the economic activities and resulted in the construction of 
massive commercial buildings along the periphery of the main roads. These strategies 
have progressed the transportation system but also generated environmental issues. 
338 
 
 
Additionally, economic interests have motivated people to build new houses close to 
the borders of commercial activities. Economic interests have played a significant role 
in progressing sprawlization and have surrounded the city with low-density of 
population and buildings. 
According to the results, agricultural and service activities account for the majority 
of employment. Industrial activities got third place. In the agricultural and service 
activities, Sari is independent and regarded as a supplier or exporter of services and 
products. The city is not a supplier of industrial activities and has a dependency. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
339 
 
 
12.2. Solutions 
One of the main drivers of urban growth is economic activities, and according to 
the results, there is a significant relationship between urban growth and the growth of 
economic activities. The growth of economic activities is equal to the growth of cities, 
so difficulties in economic activities at the regional or national levels face the local 
urban economic activities and markets with issues. And national development affects 
local and regional development directly and indirectly. So, if decision-makers provide 
some policies with adverse effects on national development and economic activities; 
as a result, the urban-rural activities will be affected negatively at the local and 
regional levels. In this regard, after the revolution of the year 1979, Iran’s economic 
structure has changed because of some dramatic changes in the political structures and 
centralization. Which changed the suply chain, imbalanced and changed the urban-
rural economic activities. As a result, these issues stopped small economic activities, 
affected rural development negatively and forced people to migrate from rural to 
urban areas. Therefore, this thesis proposes reducing the presence of government, 
semi-governmental agencies, and military forces in economic activities. Additionally, 
it is necessary to increase the presence of private sectors in economic actvities 
regardless of small or large businesses. Because, for national economic development 
and realizing urban-rural development, is necessary to have a safe market with equal 
opportunities. This strategy boosts the market and increases job opportunities in both 
urban and rural areas. This study is for the presence of government in the economy, 
but just as a controller and supporter of the market, and not more. The government 
should monitor all activities, enact required and supportive rules, and supervise during 
the implementation and execution of development plans and projects. 
In the following, further solutions were presented considering the aims of this 
thesis.  
So, the next solution is for Iran’s planning system. First, updating the urban 
development plans’ guidelines and principles are required at the national level. Just 
copying and using planning theories and principles from the industrialized countries to 
develop Iranian’s cities, is not a good idea. Because each country has its own social 
340 
 
 
and political structures. For example, "Comprehensive Plan" and "Detailed Plan," 
have been used for more than seven decades the for development of Iranian cities. But 
according to the results, neither could implement successfully in Iran. this study 
belives, successful implementation of these plans depends on doing some required 
structural changes in Iran’s planning system and political structure concerning the 
nature of these plans. 
And second, making development plans policies and strategies according to the local 
conditions by the local governments helps these plans to be implemented with more 
success. The local governments must have the main role in the planning and executing 
process. And national organizations must concentrate on the process of providing 
development plans, also monitoring during the execution.  
In this regard, for the city of Sari, it is required to provide a sustainable model of 
development plan by the local government considering the local potentials, 
weaknesses, opportunities, and threats. Otherwise, these plans could not be 
implemented successfully. Since the last decades in Sari have been implemented many 
development plans, but no one could be implemented completely and successfully. 
Because, this problem reffers to the structural issues that were explained especificlly 
in chapter nine.  
The next solution is, decentralizing the current massive centralized political system 
of Iran. Decentralization increases social-political participation in the processes of 
development, and this is the right way to decline polarization and provide equal 
opportunities for the development of urban and rural areas. Because, it is necessary to 
provide a safe space for social-political activities and enhance the role of private 
sectors and NGOs in the process of development.  
In the following, further solutions were presented for controlling the sprawl growth 
and contributing vertical growth instade of horizental growth. It is absolutely 
necessary to amend the legal barriers of the high-rise building. Because, in the 
detailed plans, constructing big buildings and contributing vertical growth is not 
allowed in this city. And this issue has reduced the density of buildings, distributed 
341 
 
 
the population horizontally, and increased demands for getting permits to construct 
new houses and apartments. As a result, these issues has increased land consumption 
because of increasing demands for new raw land parcels to construct new buildings. 
Therefore, amending this rule is neccessary to contribute High-rise buildings. It helps 
to have a compact model of city development, and reduces land-use changes and land 
consumptions.  
In the following, further solutions were presented to control the population growth 
of Sari city, which will be effective to decrease the massive migration from other 
areas to this city considering the position of Sari in this metropolitan area. According 
to the results, the urban system of the Mazandaran metropolitan area is imbalanced. 
There is a remarkable imbalance between the size and rank of cities, particularly in the 
group of the big- and medium-sized cities. But, fortunately, there is no remarkable 
imbalance in the group of small-sized cities (group A)! Hence, this thesis belives, the 
small-sized cities can play a significant role in realizing balance in this metropolitan 
area and promoting sustainable development.  
“The small-sized cities are sustainability friendly and 
attention to this group of cities is necessary!“ 
 
Figure 241Controlling the rapid regional migration to the big cities by the small-sized cities (by the author) 
But for this aim, the required infrustructures, facilities, and job opportunities must 
be provided for the small-sized cities. Because, finding a job is one of the main reason 
of the migrtation in this metropolitan area. So, if the small-sized cities besides the 
required infrustructures will be able to provide more job opportunities, it movtivates 
people to stay in this cities instate moving to the big cities. 
342 
 
 
The next solution is addressed to the legal barriers. According to the results, some 
legal barriers have created new propbelms in the city of Sari. So, the following 
amendments are necessary in the urban laws: 
1- Eliminate the law of (“ Article One Hundred” or Maddeh Sad”). As it was 
deiscussed before, this law allows people to construct new buildings or change land 
uses without getting before a permit. Therefore, untill this law exists, urban 
development plans and land use plans could not be emplimented successfully. So, It is 
necessary eliminate this law to stop this destructive and non-sustainable process. 
2- Reviewing The Height of Buildings Act. As it was deiscussed before, this act do 
not allow high-raised building. And this issue has increased the needs to the new land 
parcels. So, this thesis propopses about 30% or 40% Increase in the height of 
buildings. Increasing the density of hight is better than increasing the density of land 
parcels! It helps to use land resources efficiently and control this non-sustainable 
trend. 
And the last solution is addressed to the controlling unplanned small or big building 
projects. The people building on land parcels without respect to the road network plan 
or land use plan. Even they have started building projects in places without any 
accessibility to the water, gas and electricity networks. 
 
Figure 242 A planned building progect to control unplanned land use changes (by the author) 
 
343 
 
 
In this regard, this thesis proposes building new planned suburbs with affordable 
apartments and houses exemplarily for two or three thousand residents to control 
unplanned land subdividing and building progects. 
But this project must have the following criterias: 
- Providing an accessible and effective transportation system, 
- Providing essential required urban services and infrastructures considering per 
capita, 
- Considering environmental limitations in this project, 
- Promoting mixed-use activities considering compatibility, proximity, capacity, 
accessibility, and type of activities, 
- Increasing the density and height of buildings to use land recourse more 
effectively, 
- Building homes and apartments at an affordable price for low- and middle-
class families. 
 
Answer to the research questions considering the results and solutions: 
What are the causes of instability and increasing land-use changes in the big 
city of Sari, and what factors play a role in exacerbating it?  
Iranian cities since the last decades have been faced with uncontrolled land use 
changes issues and this challenge it is not just limited to the city of Sari. The 
following factors are the main reasons that have intensified land use changes in this 
city: 
- Disintegrity amon Iran's planning system, political structure, and social system 
- Incoordination and disagreement among the players, including enactors, 
executors, authorities, and planners, 
- Structural and functional contrasts between the nature of urban development 
plans with the nature of Iran’s political and administrative systems, 
344 
 
 
- The centralized political structure has imbalanced the national power, created 
structural problems and disintegrated the planning, political, and public sectors 
from each other structurally and functionally, 
- The ambiguities and weaknesses in the urban legislations and laws. 
How is the pattern of urban development in the Mazandaran metropolitan 
area considering the distributions of the population in the cities and place of Sari 
city in this region? 
According to the models' results, Iran's urban population growth will continue in 
the following decades. Unfortunately, the most significant part of the growth of Iran's 
urban population and also the Mazandaran metropolitan area resulted from the 
migration of people from rural to urban areas. Sectoral development strategies and the 
unequal distribution of development opportunities, infrastructures, and facilities 
between big cities have intensified noncontrolled urban-rural migrations. 
The following items indicate the current situation of the Mazandaran metropolitan 
area: 
- The urban hierarchies are imbalanced, 
- Also, the imbalance between the population size of the first big city and the 
smallest city is too much, 
- There is a strong inverse correlation between the rank and size of cities. About 
31 percent of the urban population has concentrated in just 3.3 percent of the 
total cities, and 71 percent of the population in 96,67 percent of the total cities, 
- Sari has been faced uncontrolled population growth since the last decades, 
- Sari has grown uncontrolled and scattered, and such non-sustainable land-use 
changes have faced Sari with many issues, 
- Most of the uncontrolled land use changes happened near the official border, 
- Land value plays a significant role in land-use change and land subdivision in 
this city. 
345 
 
 
What development forces have intensified land use change and consumption in 
this city, and how?  
Generally, economic forces play significant roles in the development process. 
Iran’s centralized political structure has weakened private sectors in economic 
activities and powered the Government. On the one hand, and this issue has increased 
the presence of the government particularly in cities. And on the other hand, it 
decreased the attention of the government to the development of rural areas. And his 
issue has increased urban-rural migrations and big cities like Sari have become more 
populated. The uncontrolled migrations have intensified land use changes and land 
consumptions in the city of Sari since the last decades.  
The following items have increased the migration from Medium- and Small-sized 
cities also rural areas to the big city of Sari and intensified land use changes and 
consumptions: 
- Sari city has a considerable role in providing agricultural goods also services 
and industrial activities at the national and regional levels, 
- Sari as a capital city, has the most service centers, financial centers 
administrations, health and education centers, and recreational activities, 
- Also, constructing new road networks because of economic activities have 
changed the valuable farmlands, and created environmental issues, 
- Low-density building has progressed sprawl growth. 
How can drive the uneven and destructive spatial pattern of urban 
development and intense land-use changes of Sari city toward a balanced and 
sustainable path? 
According to the results, the abovementioned issues are the main reasons for this 
city's sprawl growth and uncontrolled land use changes. Therefore the following 
solutions can help to drive the uneven and destructive spatial pattern of urban 
development and intense land-use changes in Sari city toward a balanced and 
sustainable path: 
346 
 
 
- Decentralizing the political and administrative systems and distributing power 
between all players and relevant organizations in order to decrease the 
structural and functional contrasts between the nature of urban development 
plans with the nature of Iran’s political and administrative systems 
- Increasing the structural resiliency and effectivity by maximizing participation 
in the planning, management, and policy-making process.  
- Increasing the coordination and agreement among all actors, including 
enactors, executors, authorities, and planners. 
- Increasing the structural integrity of the planning system, political structure, 
and social body. 
- Giving more power to the local organizations and authorities during the 
planning, decision-making, and execution of development projects. 
- Increasing the local participation in the planning and execution steps benefits 
their support to implement plans more successfully; and reduces the risk of 
failure by paying attention to the locals’ wishes in the planning process! 
- Equal distribution of resources, budget, development projects, and 
opportunities between the regions to control the migration from non-developed 
areas towards more developed areas, particularly big cities. 
- By controlling the migration, we would be able to control the growth of 
housing demand, control pressure on the housing market, control population 
density in the inner zones, which has pushed the surplus of population towards 
the outside, control subdividing farmlands, and control sprawl growth. 
- Paying more attention to small-sized cities is necessary. Considering the 
imbalance in the urban system of the Mazandaran metropolitan area, 
particularly in the big- and medium-sized cities, the small-sized cities can play 
a significant role in realizing balance in this metropolitan area. 
- Eliminate the law of (“ Article One Hundred” or Maddeh Sad”). It is necessary 
to stop constructing new buildings, or applying any changes in buildings, or 
even changing types of activities without permits. 
347 
 
 
- Reviewing The Height of Buildings Act. About 30% or 40% Increase in the 
height of buildings can help to use land resources efficiently and control this 
non-sustainable trend. 
- Building new planned suburbs with affordable apartments and houses 
exemplarily for two or three thousand residents can be one of the leading 
solutions to control uncontrolled land subdividing and building. 
 
And finally, the author hopes that, this thesis could provide valid and reliable 
results considering the questions and aims of this thesis. If someone want work on this 
topic in the future, I propose them to concentrate on the medium- and small-sized 
cities of the mazandaran metropolitan area. It helps to have a more hollestic view on 
the urban growth and deveopment of this metropolitan area. 
 
 
 
 
 
 
 
 
 
 
 
 
 
348 
 
 
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