A multi-factor model developed on residents' opinions for the classification of urban residential areas
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The process of social differentiation in post-communist states has had a clear impact on the status of neighbourhoods. Municipalities have tried to handle the problem, but planning in Hungary is still based on shallow analyses. This paper presents a method for examining and quantifying prevailing factors of residential areas, also being able of a spatial comparison. It detects problematic issues and locations and assists in the formulation of solutions. The model city for the presented study was Szeged, located in southeastern Hungary. Szeged is the economic center of the region and it was an ideal urban area for the evaluation of housing needs and for the mapping of various objects and social services. A field-collected qualitative database was processed using the Idrisi Selva GIS program, resulting in a classifying map of investigated areas. We have localized the properties of the lowest score and also determined the major issues responsible for low scores by analysing the spatial data of 27 GIS layers. The model can be used to detect the reasons causing differences in the perception of neighbourhoods, while it may serve as a tool for decision makers.