Planning is of vital importance for the development urban areas to facilitate sustainable economic growth and social functions. The traditional, manual ways of planning that depend on biophysical data and use a hierarchical approach are no longer appropriate for site choice since information is rapidly updated today. Multi-criteria analysis (MCA) has been used for about two decades with geographic information systems (GIS) to analyze spatial problems. GIS-based Multi-Criteria Decision Analysis (MCDA) provides tools for assessing the inherent tradeoffs and mechanisms for incorporating and documenting the value judgments of interest groups and decision makers and is thus a more reasonable and scientific way for site selection to development. Guangzhou, the study area of this paper, is one of the fastest developing and largest cities located in Southern China. This research used the GIS-based MCDA approaches to find the appropriate sites for residential areas in Guangzhou. Satellite images, DEM and several thematic maps of Guangzhou were used in this research. Using different methods and technologies, the data were used to create constraint and factor maps for multi-criteria analysis. After building the MCA model, the weights for multi-criteria analysis were obtained through an analytic hierarchy process (AHP) by comparing the importance of every two factors. Finally, a suitability map for housing development was generated. The result indicates that with the help of GIS and remote sensing technologies, the process of site selection and urban planning can be done in a more effective and scientific way. The limitation and future perspective of GIS based MCDA methods are discussed.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hig-21313 |
| Date | January 2015 |
| Creators | Wei, Da, Ding, Yijie |
| Publisher | Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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