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This work examines the use of spatial analytical techniques to explore the patterns of social exclusion. The basis for the work is a set of indices of social exclusion/inclusion for the Brazilian city of São Paulo, which have had with a major impact on policy makers and the public. We use global and local spatial autocorrelation indices to explore the properties of the social exclusion patterns in São Paulo, and to identify clusters of social exclusion and social inclusion in São Paulo. We also use spatial regression techniques, which shows that the conditioning factors of social exclusion vary considerably within the city. We have also mapped spatio-temporal trends in the evolution of crime in São Paulo using geostatistics.
Social exclusion, local spatial autocorrelation, spatial regression
Social exclusion, local spatial autocorrelation, spatial regression
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