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dc.contributorPla Bañón, Filiberto
dc.contributor.authorMegahed, Yasmine
dc.contributor.otherUniversitat Jaume I. Departament de Llenguatges i Sistemes Informàtics
dc.date.accessioned2016-01-25T08:17:04Z
dc.date.available2016-01-25T08:17:04Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10234/146445
dc.descriptionMàster Universitari en Tecnologia Geoespacial/Geospatial Technologies. Codi: SIK013. Curs: 2014/2015ca_CA
dc.description.abstractThe rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectivelyca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherUniversitat Jaume Ica_CA
dc.rights.urihttp://rightsstatements.org/vocab/CNE/1.0/*
dc.subjectMàster Universitari Erasmus Mundus en Tecnologia Geoespacialca_CA
dc.subjectErasmus Mundus University Master's Degree in Geospatial Technologiesca_CA
dc.subjectMáster Universitario Erasmus Mundus en Tecnología Geoespacialca_CA
dc.subjectUrbanizaciónca_CA
dc.subjectMapas de zonificaciónca_CA
dc.subject.lcshZoning mapsca_CA
dc.subject.lcshUrbanizationca_CA
dc.subject.otherUrbanitzacióca_CA
dc.subject.otherZonificacióca_CA
dc.subject.otherMapesca_CA
dc.titleLand cover mapping analysis and urban growth modeling using remote sensing techniques : case study : Greater Cairo Region - Egyptca_CA
dc.typeinfo:eu-repo/semantics/masterThesisca_CA
dc.educationLevelEstudios de Postgradoca_CA
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccessca_CA


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