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    Urbane Klimaresilienz und Stadtgesundheit
    (2023) Schaefer, Mathias; Nguyen, Xuan Thinh; Köckler, Heike
    Städte sehen sich zunehmend in der Verantwortung, einen resilienten Umgang mit steigenden Temperaturen, Luftverschmutzungen und extremen Wetterereignissen zu finden, um die Gesundheit und Lebensqualität der ansässigen Bevölkerung zu verbessern. Doch was bedeutet urbane Klimaresilienz und wie äußert sie sich im Stadtgefüge? Wo sind welche Maßnahmen zur Gesundheits- und Klimaresilienzförderung notwendig? Welche Rollen nehmen Wissenschaft und Planungspraxis in der gemeinsamen Ausgestaltung dieser Maßnahmen ein? Die Dissertation nähert sich diesen Fragestellungen auf der Basis von drei referierten Veröffentlichungen. Konkret werden Theorien der Resilienz und Stadtgesundheit mit transdisziplinärer Forschung vereint und am Beispiel der Stadt Dortmund neue Erkenntnisse für die Klimaanpassung aufgezeigt. Im ersten Beitrag werden urbane Klimaresilienz und sozial-ökologische Herausforderungen über die Integration einer multikriteriellen Fuzzy-Bewertung kartiert. Auf gesamtstädtischer Ebene zeigt sich, dass gewisse Stadtteile und Flächennutzungen anfälliger für Klimaextremereignisse und Umweltbelastungen sind. Darüber hinaus kann beobachtet werden, dass mehrfach umweltbelastete Bereiche mit potenziell weniger vulnerablen Anwohnern existieren und umgekehrt. Im zweiten Beitrag wird die Hitzebelastung und Feinstaubverteilung im Quartier Dortmund-Marten näher untersucht. Hierfür wird die subjektive Wahrnehmung von Passanten an zwei Straßenzügen während eines heißen Sommertags erfasst und sowohl mit Feldmessungen als auch mit mikroklimatischen Simulationen überprüft. So lässt sich festhalten, dass Fußgänger an beiden Straßenzügen abwechselnd einem der beiden betrachteten Stressoren im Tagesverlauf gegenüberstehen. Mehr als die Hälfte der Passanten empfindet ein thermisches Unbehagen, wohingegen kein klarer Trend zu einer subjektiv wahrgenommenen Feinstaubbelastung festgestellt wird. Kernthema der dritten Kontribution ist die Evaluation eines projektbasierten Workshops zwischen Wissenschaftlern und Stadtplanern zur Erarbeitung von Begrünungsmaßnahmen in Dortmund-Marten. In einer anschließenden Online-Befragung zum Workshop ist der selbst eingeschätzte Wissenszuwachs der teilnehmenden Forscher höher als bei den Planungspraktikern, während sich die Vermittlung des individuellen Fachwissens für die Forschenden vergleichsweise schwieriger gestaltet. Die potenziellen Auswirkungen der erarbeiteten Maßnahmen äußern sich in einem ambivalenten Verhältnis zwischen einer großflächigeren Feinstauberhöhung und kleinräumigeren positiven Effekten hinsichtlich des Thermalkomforts. Die Zusammenführung der theoretischen und praktischen Erkenntnisse verdeutlicht die innewohnende Komplexität des Resilienzgedankens, welche sich nicht nur in der Umsetzung räumlicher Analysen, sondern auch in der kooperativen Zusammenarbeit zwischen Wissenschaftlern und Stadtplanern zur Maßnahmensetzung niederschlägt. Die Ergebnisse sind daher nicht nur für die Wissenschaft, sondern auch für die Planungspraxis von Bedeutung. Sie geben Hinweise auf methodische Fallstricke und bieten eine nützliche Informationsgrundlage für den integrativen und transdisziplinären Austausch im Sinne einer klimaresilienten und gesundheitsfördernden Stadtentwicklung.
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    Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens
    (2022-08-09) Schaefer, Mathias
    Green Infrastructure (GI) is gaining wide recognition in cooperative research projects seeking to find solutions for climate adaptation in urbanized areas. However, the potential effects of co-produced GI plans and the underlying preparation process are rarely evaluated. To bridge this gap, the aim of this article is to examine what works in addressing environmental burdens in the urban neighborhood of Dortmund Marten, Germany. As part of a larger transdisciplinary process, selective GI measures were delineated in the case study area through a cooperative workshop between scientists and urban planners. Workshop ideas were incorporated into a mitigative scenario considering a hot summer day to quantify the effects of the derived GI measures on thermal comfort and particulate matter dispersion (PM10 and PM2.5). To evaluate the experiences of the science-practice collaboration, the viewpoints of researchers and urban planners on learning effects, knowledge integration, and GI planning were summarized and compared via an online survey. The results indicate that the proposed GI measures could reduce physiological equivalent temperature (PET) by 25 °C. At the same time, additional roadside trees could increase PM10 concentrations by up to 36 µg/m3 due to wind blocking effects. Reflections on the science-practice workshop show that learning effects were higher for the participating researchers than for planning practitioners, while the integration of individual expertise during the workshop was more difficult for academics. These findings point to the importance of continuous reflections on individual understandings in cooperating stakeholder groups and the value of the evaluation of outcomes in transdisciplinary GI planning.
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    Streamflow simulation in data-scarce regions using remote sensing data in combination with ground-based measurements
    (2022) Baez Villanueva, Oscar Manuel; Thinh, Nguyen Xuan; Ribbe, Lars
    Global water resources are currently under unprecedented stress, which is projected to increase due to the influence of multiple factors. Therefore, changes in governance are urgently required to improve water management and water use efficiency while maintaining the health of river systems and their water quantity and quality. Data is crucial in this process; however, most rivers in the world remain ungauged, and in data-scarce regions, the hydrometric and hydrometeorological networks of stations have been decreasing during the last decades. This hinders the implementation of proactive water management approaches that strive towards informed-based decision-making. This cumulative thesis shows how open access global precipitation products can be evaluated, corrected, and used to predict streamflow at the daily temporal scale in data-scarce regions in combination with ground-based measurements by following a three-step approach: i) performance evaluation of different precipitation products over regions with different climates and at multiple temporal scales; ii) development of a novel merging method to improve the representation of precipitation at the daily scale; and iii) assessment of the ability of the novel merged product altogether with state-of-the-art precipitation products to predict daily streamflow over ungauged catchments through the implementation of regionalisation approaches. This thesis showed that the precipitation products perform differently depending on the temporal scale, elevation, and climate; and that these products still have errors in detecting particular precipitation events. These insights served as a basis to develop a novel merging procedure named RF-MEP, which combines data from precipitation products, ground-based measurements, and topographical features to improve the characterisation of precipitation. RF-MEP proved to be a powerful method as the precipitation errors at different temporal scales were substantially reduced, outperforming state-of-the-art precipitation products and merging procedures. The precipitation product derived with RF-MEP has been included in a Chilean precipitation monitor platform from the Center for Climate and Resilience Research (Mawün) and users can apply this method in a friendly manner using the R package RFmerge. This merged product altogether with three state-of-the-art precipitation products was used to implement three regionalisation approaches by calibrating an HBV-like hydrological model over 100 near-natural catchments in Chile. The results showed that although these methods yielded relatively good performances, the precipitation products corrected with daily gauge observations did not necessarily yield the best hydrological and regionalisation performance. Additionally, the hydrological regime of the catchments influenced the performance of the evaluated regionalisation techniques, with the pluvio-nival and raindominated catchments yielding the best and worst performance, respectively. This cumulative dissertation shows that precipitation datasets can help to strive towards informed-based decision-making in data-scarce regions. However, these regions often lack the infrastructure and human capacity to use this type of information efficiently. Therefore, an informed-based decision-making process requires institutional transitions and changes that help address water resources management’s present and future challenges. In this sense, there is a need to move towards data-driven water resources management by implementing strategic approaches that systematically build the capacities and infrastructure of such regions.
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    Investigating the relationship between: urban identity, quality of urban life, and urban physical form in Iranian new towns
    (2021) Derakhshan, Mahsa; Thinh, Nguyen Xuan; Baumgart, Sabine
    New Towns in Iran have been located, planned, and built near the big cities since early 1981 to attract the overflow population of metropolises and reduce the density of the mother cities. Andisheh is one of the Iranian new towns that was built in 1992 in a 30 kilometers distance from the metropolis of Tehran. Despite the efforts of the planners and urban designers in locating new towns, and designing open spaces, squares, streets, parks, appropriate width of roadways, and residential complexes, new towns lack something. Their urban spaces are not attractive for their inhabitants, residents are not satisfied with the quality of the urban environment and they tend to leave new towns. Moreover, most of the new towns are faced with such problems as being a dormitory for their residents. It is important to study the quality of urban life and urban identity related to physical form in urban areas such as new towns since urban physical form affects perceptual aspects of residents, so perceived quality of life, sense of belonging, and sense of place. Human perception and experience of their surrounding urban spaces and QOUL affect the behavior of residents. Urban identity is related to the identity of residents and also the identity of the city. The urban environment reflects its resident’s needs and values and all of the residents are part of their cities, because, without citizens, the cities would not be what they are. The present research investigates the relationship between the quality of urban life (QOUL), urban identity (UI), and urban physical form (UPF) in Andisheh new town focusing on density, housing, land use, layout, and accessibility. This study includes descriptive, analytical, and explorative research, in which a mixed-method approach including the qualitative and quantitative methods – a case study approach and a quantitative descriptive method- is utilized. The methods used in this research are (1) the literature review and theoretical analysis, (2) questionnaire to survey the case study with a sample of 413 questionnaires filled by residents, (3) the qualitative method to obtain fundamental knowledge and to collect information through the interview with urban experts, (4) quantitative method, to collect numeric and statistical data and finally, (5) Space Syntax analysis, GIS, and statistical methods including SPSS using KMO and Bartlett’s Test of Sphericity and CFA, and SEM (structural equation modeling) through AMOS. The Space Syntax Theory is employed by measuring the value of connectivity, integration, and mean depth. GIS has been used to evaluate the spatial scattering of land uses, and geocode the locations of the residents (through their addresses), and creating a set of geodatabase containing all the questions of questionnaires. Data collected through questionnaires and geocoded in GIS has been analyzed through SPSS and AMOS. The SEM is applied to analyze the relationship between indicators of QOUL, UI, and UPF, as well as, the correlation between these dimensions. The hypotheses of this study, which are the main hypotheses of the research (HI and HII) and subsidiary hypotheses (H1- H9) related to each dimension, are analyzed through SEM analysis. The value of the path coefficient represents that if there is a positive, negative, or no significant correlation between variables. Therefore, the results of SEM analyses indicate two types of acceptable or not significant correlation. The acceptable positive correlations are between: dimensions of UI and QOUL with the value of 0.87 (HI), objective measures of housing and satisfaction with housing with the value 0.32 (H2), activities and meaning with the value 0.12 (H4), objective measures of housing and objective measures access with the value 0.48 (H7), objective measures of housing and objective measures of land use with the value 0.52 (H7), objective measures of housing and objective measures of density with the value 0.42 (H7), objective measures of access and objective measures of land use with the value 0.39 (H7), subjective measures of access and overcrowding with the value 0.57 (H8), subjective measures of layout and overcrowding with the value 0.61 (H8), and subjective measures of access and subjective measures of layout with the value 0.77 (H8). The negative acceptable correlations are between: UF and QOUL with the value -0.64 (HII), UF and UI with the value -1.30 (HII), objective density and satisfaction with overcrowding with the value -0.53 (H1), mean depth and satisfaction with land uses -0.22 (H6), and between objective measures of land use and objective measures of density with the value - 0.61 (H7). The results represent that there is not a significant correlation between: objective density and perceived overcrowding (H1), objective measures of land use and satisfaction with land use (H3), physical setting and meaning (H4), physical setting and activities (H4), objective measures of accessibility and subjective measures of accessibility (H5), objective measures of access and objective measures of density (H7). It is significant to note that the results and findings are based on the questionnaires that were filled out by the residents of Andisheh new. Therefore, the correlations between variables may have a different outcome in other cities. As a summary of the conclusion of the present research in Andisheh new town, it can be pointed out that although there may not be a significant relationship between some indicators of UI, QOUL, and UPF, but in general, there is a strong relationship between UI and QOUL in Andisheh new town. Moreover, UPF affects UI and QOUL, and this relationship is strong and negative. Keywords: quality of urban life (QOUL), urban identity (UI), urban physical form (UPF), geocoding the location of residents, analysis of population and density/ housing/ accessibility/ urban layout/ and land use, Space Syntax analysis, structural equation modeling (SEM), the relationship between indicators of UI, QOUL, and UPF
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    How can climate resilience be measured and visualized?
    (2020-01-15) Schaefer, Mathias; Thinh, Nguyen Xuan; Greiving, Stefan
    As negative impacts of climate change tend to increase in the future, densely-populated cities especially need to take action on being robust against natural hazards. Consequently, there is a growing interest from scientists in measuring the climate resilience of cities and regions. However, current measurements are usually assessed on administrative levels, not covering potential hotspots of hazardous or sensitive areas. The main aim of this paper focusses on the measurement of climate resilience in the City of Dortmund, Germany, using Geographic Information Systems (GIS). Based on a literature review, we identified five essential components of climate resilience and initially designed a theoretical framework of 18 indicators. Since climate resilience is still a vague concept in scientific discourses, we implemented local expert knowledge and fuzzy logic modelling into our analysis. The benefit of this study not only lies in the fine-scale application, but also in the relevance for multiple disciplines by integrating social and ecological factors. We conclude that climate resilience varies within the city pattern, with the urban core tending to be less resilient than its surrounding districts. As almost the entire geodata set used is freely available, the presented indicators and methods are to a certain degree applicable to comparable cities.
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    Investigation of the impacts of urban land use patterns on energy consumption in china
    (2017-08-07) Zhao, Jie; Thinh, Nguyen Xuan; Li, Cheng
    Urban land use patterns are increasingly recognized as significant contributors to energy consumption. However, few studies have quantified the impacts of urban land use patterns on energy consumption. In this study, we analyzed the impacts of urban land use patterns on energy consumption for 20 provincial capital cities in China from 2000 to 2010. Landsat data and spatial metrics were first used to quantify the urban land use patterns, and then city-level energy consumption was estimated based on nighttime light (NTL) data and statistical provincial energy consumption data. Finally, a panel data analysis was applied to investigate the impacts of urban land use patterns on energy consumption. Our results showed that NTL data were effective for estimating energy consumption at the city level and indicated that accelerated energy consumption was caused by increases in the irregularity of urban land forms and the expansion of urban land. Moreover, significant regional differences in the impacts of urban land use patterns on energy consumptions were identified. Our results provide insights into the relationship between urban growth and energy consumption and may support effective planning towards sustainable development.
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    Urban growth monitoring, simulation and management from coastal cities management perspective using Cellular Automata, Remote Sensing and GIS: a case study of Alexandria governorate, Egypt
    (2019) Elmorshdy, Mustafa Ahmed Mustafa; Thinh, Nguyen Xuan; Wegener, Michael
    Egyptian coastal cities are astonishing places for people to live. Due to lack of adequate sustainable management and governance, the coastal cities and its resources suffer from multitude of negative environmental impacts, particularly uncontrolled urban growth. By the means of Landsat satellite imagery, remote sensing and GIS, Multi-temporal and spatial analysis for the investigation area has been conducted for the last three decades. Results showed that there are disparities between land-use practices and coastal zone management and spatial planning policies governing the coastal cities. Furthermore, the encroachment of agriculturally productive land and parts of freshwater resources (Lake Mariute) resulting in new urban areas. The author and with help of 23 urban decision-makers have proposed driving factors of urban growth for the study area. Thereafter, urban growth monitoring and prediction were conducted using a standalone CA-based model that was developed by the means of Python programming language. Definition of the transition rules through calculation of the transition potential was conducted. Monte Carlo method was used to calibration the model, in which, the parameters’ calibration process takes place through probability distribution for each used parameter in the calibration process. Figure or Merit and overall agreement as precision indicators resulting accuracy range from 87.6% to 90% goodness-of-fit. Five scenarios to predict urban growth for the year 2032 were developed. Multiple Criteria Decision Making (MCDM) was implemented through the integration of two techniques; Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC), aiming at defining land suitability criteria and weights for the new urban areas. The results indicated that maximum environmental protection and compact city growth scenarios are the closest to the strategic urban plan for Alexandria 2032 and also have a low influence on the cultivated lands.
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    Assessment of the effects of urban expansion on terrestrial carbon storage
    (2018-02-28) Cheng, Li; Zhao, Jie; Thinh, Nguyen Xuan; Xi, Yantao
    Carbon storage is closely connected to the productivities and climate regulation capacities of ecosystems. Assessing the effects of urban expansion on carbon storage has become increasingly important for achieving urban sustainability. This study analyzed the effects of urban expansion on terrestrial carbon storage in Xuzhou City, China during 2000–2025. The cellular automata (CA) model was developed to simulate future urban expansion under three scenarios, namely, the business as usual (BAU), ecological protection (ECO), and planning strengthened (PLS) scenarios. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was further applied to explore the consequences of urban expansion on carbon storage. The results show that urban expansion resulted in 6.099 Tg of carbon storage loss from 2000–2015. Moreover, significant differences in the effects of the urban expansion scenarios on carbon storage were identified in terms of both magnitude and spatial pattern from 2015–2025. Compared with the other scenarios, the PLS scenario could be considered as a good option that would allow future development to achieve the objectives of the lowest carbon storage losses. The findings improve the understanding of the effects of urban expansion on carbon storage and may be used to support urban planning and management.
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    Spatio-temporal variation analysis of landscape pattern response to land use change from 1985 to 2015 in Xuzhou City, China
    (2018-11-19) Xi, Yantao; Thinh, Nguyen Xuan; Li, Cheng
    Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.
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    Study of vegetation cover change and its driving forces
    (2019) Xu, Yong; Thinh, Nguyen Xuan; Bill, Ralf
    The dynamic change of vegetation cover exerts significant influences on the energetic and chemical circulation worldwide. Systematically monitoring the global vegetation cover change is critical to promote a better understanding of the basic biogeochemical processes, and their possible feedbacks to the global climate system. It is of great practical value to study dynamic vegetation variation related to climate change, human activities, and natural factors to explore the underlying relationships between vegetation cover change and its driving forces and the responding mechanisms of vegetation cover to the variability of the driving forces. Vegetation degradation is continually proceeding worldwide, but the degradation situation is more serious in developing countries than in developed countries. China is the largest developing country, and it has been experiencing significant socio-economic development, rapid urban expansion, and sharp population growth in eastern China in particular after launching the program of reform and opening-up termed "Socialism with Chinese Characteristics" in China in 1978. The unprecedented socio-economic development, urban expansion, and population growth have led to land use and land cover change, soil fertility decline, vegetation degradation, water contamination, and biodiversity loss in eastern China. Eastern China, a place with a highly developed socioeconomic status than other regions of China, covers seven provinces (e.g., Liaoning, Hebei, Shandong, Jiangsu, Zhejiang, Fujian, and Guangdong) and three municipalities (e.g., Beijing, Tianjin, and Shanghai) with an area of about 1.0277 million km2. It is of critical importance for monitoring the dynamic vegetation variation on multi-spatiotemporal scales, exploring the underlying relationship between vegetation cover change and its driving forces (e.g., climate forces, topographic forces, and socio-economic forces), and investigating the time lag effects of vegetation variation in response to climate variables (e.g., precipitation and temperature) in eastern China from 2001 to 2016. To achieve the objectives of this study, the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (NDVI) time series with a 250 m spatial resolution and a 16-day temporal resolution, monthly meteorological data from meteorological (automatic) base station , Digital Elevation Model data with a 30 m spatial resolution, socio-economic statistical data, and the map of land use types, gross domestic product, and population density in 2000 and 2015 with an 1 km spatial resolution, and the vector map of eastern China at city level were used. A set of mathematical methods such as the maximum value composite method, linear regression analysis, rescaled range analysis, coefficient of variation, Person’s correlation coefficient, t-test, and spatial analysis methods (e.g., surface analysis and overlap analysis) were applied in this study. This study aims at monitoring the dynamic change of vegetation cover and investigating the relationship between vegetation cover and its driving forces on multiple spatiotemporal scales in eastern China from 2001 to 2016. The objectives of this study are fulfilled and the main findings and new results of this study are summarized in following. The overall annual NDVI displays a distinctive spatial heterogeneity across eastern China, presenting a gradient decrease from the south to the north of eastern China. The spatial distribution of NDVI in spring, summer, and autumn follows a similar pattern, but the overall NDVI value is higher in summer than in spring and autumn. Our calculation indicated that, during the past 16 years, the vegetation cover had gradually increased in eastern China with a magnitude of 0.0003 year-1. Areas with a greening trend and areas with a browning trend account for 49% and 33% of the study area, respectively. Spatially, we found that the browning areas are mainly distributed in city centers and the three economic zones and its surrounding areas. Considering the vegetation variation on seasonal scale, NDVI performs an increasing trend in spring and autumn but a decreasing trend in summer. In this study, we detected that areas expected to show consistency accounting for a larger proportion when compared with the areas expected to show anti-consistency on annual scale, while an opposite phenomenon was found on seasonal scale. In terms of the future changing trend of vegetation cover, areas with certain vegetation degradation will be larger than areas with certain vegetation improvement for eastern China both on annual and seasonal scales in the future. Estimating the vegetation stability on the basis of variation of coefficient, we found that the vegetation cover is relatively stable in the south of the study area, but it fluctuated wildly in the north of the study area. Our calculation suggested that temperature can be considered as the dominant climate factor controlling the vegetation growth in eastern China. The relationship is more pronounced between NDVI and temperature than between NDVI and precipitation both on annual and seasonal scales in eastern China for the study period. Moreover, the relationship between NDVI and precipitation is higher in autumn than in spring and summer, while the response of NDVI to temperature is stronger in spring than in autumn, followed by in summer. In this study, we observed, spatially, the overall maximum correlation coefficients between NDVI and precipitation as well as NDVI and temperature are basically higher in the north and lower in the south of the study area both on annual and seasonal scales. Temporally, on annual scale, the NDVI shows no lag time to changes in temperature but a 1-month lag time to precipitation variation. On seasonal scale, the maximum responses of NDVI to changes in precipitation and temperature establish 1-month longer in summer than in spring and autumn. Spatially, the lag time for maximum NDVI response to precipitation and temperature gradually increase from the north to the south of the study area. Elevation is regarded to be a dominant factor affecting the vertical distribution of vegetation cover. Our findings indicated that both the vegetation cover and vegetation stability increase with the elevation increase and reach its peak at an elevation of about 500 m. The vegetation degradation is more serious at the elevation range of 0 to 100 m than at higher elevation ranges. It is worth noticing that, in this study, our result is against our initial assumptions that the vegetation growth on the north-facing slope is better than the vegetation growth on the south-facing slope. However, we found that the vegetation cover, vegetation cover change, and vegetation stability show no statistical difference on the south-facing slope and north-facing slope. Similar to the responding mechanisms between the elevation-vegetation cover and elevation-vegetation stability, the vegetation cover and vegetation stability show a gradient upward trend with slope range increase. Furthermore, the proportion of the areas with a greening trend shows a “humped” pattern with the slope range increase, and it reaches the peak at the slope range of 6° to 15°. Our findings indicated that vegetation degradation is generally attributed to socio-economic development, urban expansion, and population growth, particularly in Tianjin, Shanghai, Jiangsu, Zhejiang, Fujian, and Guangdong. However, implementing large-scale reforestation and afforestation programs such as the Natural Forest Conservation Program, Three-North Shelter Forest Program, Beijing and Tianjin Sandstorm Source Controlling Program, and Grain for Green Program contribute to the vegetation greening phenomenon since 1978, in Liaoning, Beijing, Shandong, and Hebei in particular. We further observed that, spatially, the dynamic change of vegetation cover is negatively coupled with socio-economic development, urban expansion, and population growth. Areas with a high-speed socio-economic development, rapid urban expansion, and sharp population growth are along with severe vegetation degradation and strong vegetation oscillation spatially.
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    Combination between land suitability evaluation and multi-objective optimization mathematics model to sustainable agricultural land use planning in the coastal zone of the Mekong Delta, Viet Nam
    (2019) Nguyen, Huu Kiet; Thinh, Nguyen Xuan; Bill, Ralf
    Land evaluation is the primary content in the land-use planning process. There were many land evaluation methods which have been improved based on the FAO framework, but most of them have not been effectively assessed. The requirements of land characteristics and physical conditions supply a common view of land use types for land suitability. It is difficult in precise decision making for agricultural planning. Decision makers have to optimize productive agriculture and promote farmers’ socio-economic conditions. The obstacle of the decision makers is the uncertainty because most criteria have interactive features in reality. The simulation of land-use options is essential to support decision makers. It helps to evaluate and adjust the effects of plans because the parameters in reality are always changing. It is an excellent solution to maximize land-use efficiency. Besides, combining modelling approaches in land use planning is necessary because every approach with its single effectiveness cannot entirely assess the different parameters of sustainable land-use planning. Considering these challenges and limitations in the last studies, this dissertation aims for the development of a methodology for the monitoring and analysis of the combination between land suitability evaluation and a multi-objective optimization mathematics model to support effective land use planning towards sustainable agricultural land use planning in the coastal zone of the Mekong Delta, Vietnam. The Mekong Delta (MD) in Vietnam has faced severe risks from the significant change of ecological systems. Especially, saltwater intrusion, sea level rise and the increasing hydroelectricity dams have sharply impacted land use. One of the significant modifications is the change from rice cultivation to shrimp cultivation where the fresh water zones are converted to brackish water zones. As an inevitable consequence, it leads to advantages and disadvantages as outcomes for the economy, society and environment which strongly affect the livelihood of farmers. So four coastal districts of Soc Trang province, the MD in Vietnam were chosen as the case study. By comparing four evaluation methods in the crisp environment (FAO-, MCE-Method) and the fuzzy environment (methods of MAX operator and LUKASIEWICZ operator), we could find that the method of LUKASIEWICZ operator is the best method for land suitability analysis. The fuzzification via membership functions for four linguistic terms of suitability classification was used. The results reflect the mathematical cardinality of the LUKASIEWICZ operator in the fuzzy environment because this operator integrates all characteristics. Therefore, this method is useful in the land evaluation. The LUKASIEWICZ operator in the fuzzy environment is applied in sustainable land evaluation. The objectives of the economy, society, environment and natural resources are considered for sustainable land evaluation. The LUKASIEWICZ operator coordinated the preferences of multi-objectives and continuously expressed the suitability classification in the fuzzy environment. By comparing three results of land suitability analysis: land physical suitability (by FAO method), economic suitability (by the method of LUKASIEWICZ operator) and land sustainable suitability (by the method of LUKASIEWICZ operator), we can confirm the effectiveness of sustainable land evaluation. As a necessity, it should be applied in advanced studies in sustainable land use planning. For this study area, it can be strongly recommended for agricultural land use planning during a ten year period as a master plan. The application of FAHP (Fuzzy Analytic Hierarchy Process) for multiple criteria decision-making is based on fuzzy pair-wise comparison matrices. The result illustrates that it incorporated the preferences of nine decision makers (DMs) by weights as a compromise index. FAHP proved a useful role in multiple criteria decision-making. It is an important tool for making decision by connecting and satisfying multiple criteria of land use planning . The FMOLP (Fuzzy Multi-Objective Linear Programming) is satisfied with the conflict of qualitative and quantitative interests of five objectives (Income, Benefit per Cost ratio, Employment, Land and Environment). We established eight scenarios to find a suitable result by the alternative priorities of five objectives. The result allocates spatial planning for 5 LUTs (Land Use Types) and handles the problem of optimization to support better agricultural land use planning. It creates a balance between the land use supply and demand for land use change. This study suggests changing land use planning by Scenario 2 (More priority for economic and environmental protection development) for the 2020-2025 period in this study area.
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    Evaluation of land cover change and agricultural protection sites: a GIS and Remote Sensing approach for Ho Chi Minh City, Vietnam
    (2019-05-23) Schaefer, Mathias; Thinh, Nguyen Xuan
    Ho Chi Minh City (HCMC), economic center and most populous city of Vietnam faces a strong structural change since its market liberalization in the late 1980s. Big challenges occur in the form of uncontrolled urban sprawl due to rapid population growth with encroachment of agricultural land, which leads to environmental and climatic issues like urban heat island effects, air pollution and flooding events. Remote Sensing and Geographic Information Systems (GIS) provide new computer-based technologies for urban planners which can greatly ease the monitoring of agricultural loss as well as improve decision making for future land management. In the first part of this study, land cover change dynamics are thoroughly assessed using moderate and high spatial resolution satellite imagery (Landsat and SPOT) over the period 2010–2017 in 22 districts of HCMC. In the second part, the land cover classification results of 2017 provide the initial map for a GIS-based Multi-Criteria-Decision-Analysis (MCDA) of potential agricultural protection sites. Therefore, criteria of climate adaptation and ecological service are established and embedded in the GIS-compatible Compromise Programming Model (CP). With the use of Analytic Hierarchy Process (AHP) by Thomas L. Saaty and additional expert knowledge, appropriate weighting factors have been affiliated. The results show that agricultural land decreased by more than two thirds in the period considered. However, particularly the western rural districts Bình Chánh and Hóc Môn still offer a great amount of valuable agricultural land suitable for protection. The proposed method can serve as a scientific framework for planning departments of fast growing cities to zone agricultural land for protection on an early planning stage in order to ensure sustainable land use development in the future.
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    Urban flood simulation and integrated flood risk management
    (2017) Yang, Mu; Thinh, Nguyen Xuan; Schanze, Jochen
    Climate change induces the probability of occurring natural disasters; e.g. floods, Sea Level Rise, Green House Gases. Flood is considered one of the most dangerous phenomena that tremendously and dramatically threatening the human being and environment worldwide. Rapid urban growth, demographic explosion, and unplanned land uses have exacerbated the problem of urban flooding, particularly in the cities of China. In addition to that, the concept of flood risk management and adaptation measures and strategies are still missed in the cities’ development future plans. The main objective of this Ph.D. dissertation is to investigate the flood risk analysis and assessment based on flood simulation and adaptive strategies for flood event through two case studies of Changsha city in south-central China. In case study I, fluvial flooding was considered on mesoscale and an MCA-based approach was proposed to assess the integrated flood risk of Changsha central city. HEC-RAS 1-D model was used to simulation the inundation characteristics for hazard analysis based on four risk dimensions: economic, social, environmental, and infrastructural risk. For infrastructural dimension, apart for direct damage on road segments, network analysis method was combined with inundation information and macroscopic traffic simulation to evaluate the impact on traffic volume as well as a decrease of road service level. Closeness centrality weighted with a travel time of pre- and after- flood was compared in order to measure the impact on urban accessibility. Integrated risk values were calculated using various weighting criteria sets. Sobol' indices were used as a tool of spatially-explicit global Uncertainty Analysis and Sensitivity Analysis (UA/SA) for damage models. In case study II, an agent-based modeling approach was proposed to simulate the emergency pluvial flood event caused by a short-time rainstorm in local areas of cities aiming at developing an interactive flood emergency management system capable of interpreting the risk and reduction strategy of the pluvial flood. The simulation integrated an inundation model with microscopic traffic simulation. It also reveals that all agents can benefit significantly from both engineering measures and the only pedestrian obtain relatively more benefits from risk warning with high awareness. The method provided potentials in studies on the adaptive emergency management and risk reduction, help both decision-makers and stakeholders to acquire deeper and comprehensive understanding of the flood risk. This Ph.D. study has investigated holistic methods and models’ selection in flood risk assessment and management to overcome data deficiency and to achieve the integration of different data. The results of the first case study reveal that the integrated methods have proved to be able to improved flood risk analysis and assessment especially for indirect damage of infrastructural system with network features. The global UA/SA based on Sobol' method and visualization with maps enable to gain the spatial distribution of uncertainty for various factors, the validation of damage models, and deeper and more comprehensive understanding of flood risk. Then based on the integrated risk assessment, functions of spatial planning in flood risk management were discussed, potentially providing guidance and support for decision-making. The results of the second case study denote that agent-based modeling and simulation can be effectively utilized for flood emergency management. Two scenarios focusing on specific risk reduction interventions were designed and compared. Engineering measures by improving capability of the drainage system and the surface permeability of waterlogging areas are the most effective means for damage mitigation. High public risk awareness still has great potential benefits of the in the event of emergencies, which can greatly enhance the effectiveness of the official warning. The agent-based modeling and simulation provided an effective method for analyzing the effectiveness of different strategies for reducing flood risk at the local scale and for supporting urban flood emergency management. The case studies also indicate the significance and necessity of establishing a platform and database to realize full sharing and synergies of spatial information resources for flood risk management, which is a vital issue to manage the urban flood risk and take effective measures correspondingly with responding to emergency extreme flood event. Keywords: urban flood; flood risk assessment; network analysis; flood simulation; flood risk management
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    Translating climate science into policy making in the water sector for the Vu Gia- Thu Bon River Basin
    (2018) Tran, Tra Van; Thinh, Nguyen Xuan; Greiving, Stefan
    Vu Gia- Thu Bon River Basin, located in the Central Coastal Zone of Viet Nam faces water shortage problems. This is expected to be further exacerbated in the future as a result of climate change. Previous attempts in addressing water shortage in the area followed a traditional top-down, predict-then-act approach. In such an approach, General Circulation Model outputs simulating future climate conditions are downscaled then adaptation measures proposed. This approach could produce optimal adaptation solution under an intended future. However, given the uncertainties related to GCMs, the approach fails to provide satisfactory information for adaptation measures. This study utilizes a combined top-down and bottom-up climate change impact assessment instead. A MIKE BASIN water balance model is used to analyze the water system response in the Vu Gia- Thu Bon River Basin under different rainfall and temperature ranges. Problematic conditions were then identified. Outputs from 25 GCMs were used to map the vulnerability space of the water system onto possible future climate conditions. A more detailed analysis of the system is thus performed only on problematic conditions suggesting both by the MIKE BASIN model and the GCM outputs. An analysis of the effects of current land use policy was performed to assist in the understanding of the changes in land policy and its effect on water usage. This was done through analyzing satellite images between the years 2011 and 2016 during the land use master plan period of 2011-2020. The results obtained in the study suggest that at a minimum, 66.36 km2 of agricultural area would be facing water challenges in the future. Under more severe climate change conditions, up to 87.77 km2 of crops would be facing water shortages. Overall, there is a water deficit of between approximately 11 million and 21 million m3 of water for agricultural production. To meet the demand, the study proposes two lines of action, namely conserve/reduce use of water, and production of additional water. Conserving/reducing water usage could be achieved through changing crop types, irrigation practice, and introducing water efficient technologies. On the other hand, production of additional water includes the construction of more water reservoirs as well as to look into options such as seawater desalination.
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    Analysis of urban form parameters with a focus on energy consumption
    (2016) Zhao, Jie; Thinh, Nguyen Xuan; Bill, Ralf
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    Assessment of renewable energy potentials based on GIS and RS
    (2015) Zhang, Jie; Thinh, Nguyen Xuan; Gruehn, Dietwald