Abstract

The spatial patterns in socioeconomic and environmental data reveal issues and trends that would otherwise be missed by data aggregation to political or other units. Geographic Information System (GIS) tools display analysis capabilities that are increasingly utilized by many social scientists. This paper presents the results of spatial socio-economic (SES), environmental and accessibility analysis of Tehran city. Use of census data, satellite images, quantitative GIS, GIS mapping and statistical analysis are powerful tools to investigate the variability of these variables among 117 municipality divisions of Tehran city. Variations are described by attaching attributes to a set of 117 zones in Tehran city. A multivariate analysis applying principal component analysis for 117 zones extracted four components: (1) housing and expertise of the residents, (2) Environmental conditions, (3) Accessibility to urban services, and (4) Unemployment levels. Results show that spatial autocorrelation and spatial heterogeneity are detected in the spatial distribution of urban components in Tehran city, and therefore intra-urban inequalities exist with respect to four urban components. Understanding of these variations can help to develop more realistic models, which are critical for land use, environmental and transportation planning.