Spatial data analysis

This review is a comprehensive introduction to the intricacies of spatial data analysis, addressing historical developments, methodological advancements and practical applications utilizing software for geographical data analysis. It encompasses a wide range of topics to illustrate the significance of spatial context in modeling social phenomena, including geographically weighted regression (GWR)regression models for spatial data, spatial autocorrelation and various forms of spatial weights. Also included is an exploration of software tools like GeoDa for spatial data analysis, illustrating practical pathways from visual mapping to spatial regression.

The work is positioned against a backdrop of increasing availability and sophistication in geospatial data and analysis tools, stressing the importance of spatial perspectives in understanding social phenomena. Spatial data analysis invites for a continued exploration of how spatial perspectives can illuminate complex societal dynamics in an increasingly data-driven world.