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

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dc.contributor.advisorThinh, Nguyen Xuan
dc.contributor.authorElmorshdy, Mustafa Ahmed Mustafa
dc.contributor.refereeWegener, Michael
dc.date.accepted2019-11-29
dc.date.accessioned2020-01-07T09:37:25Z
dc.date.available2020-01-07T09:37:25Z
dc.date.issued2019
dc.description.abstractEgyptian 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.en
dc.identifier.urihttp://hdl.handle.net/2003/38492
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-20411
dc.language.isoende
dc.subjectCellular Automataen
dc.subjectUrban growth simulationen
dc.subjectLand-use/cover change detectionen
dc.subjectLand suitability analysisen
dc.subjectStrategic environmental assessmenten
dc.subjectSustainable developmenten
dc.subjectCoastal Zone Managementen
dc.subject.ddc710
dc.subject.rswkZersiedlungde
dc.subject.rswkSimulationde
dc.subject.rswkStadterweiterungde
dc.subject.rswkFlächennutzungde
dc.subject.rswkStrategische UmweltprĂĽfungde
dc.subject.rswkNachhaltigkeitde
dc.subject.rswkKĂĽstenschutzde
dc.subject.rswkFernerkundungde
dc.subject.rswkZellularer Automatde
dc.titleUrban growth monitoring, simulation and management from coastal cities management perspective using Cellular Automata, Remote Sensing and GIS: a case study of Alexandria governorate, Egypten
dc.typeTextde
dc.type.publicationtypedoctoralThesisde
dcterms.accessRightsopen access
eldorado.secondarypublicationfalsede

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