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Exploratory spatial data analysis

In: Handbook of Spatial Analysis in the Social Sciences

Author

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  • Ran Wei

Abstract

In this chapter, I discuss a core set of exploratory spatial data analysis (ESDA) techniques that are most widely used in social science. I start with choropleth maps for describing spatial distribution and detecting spatial outliers. This is followed by an introduction of a few global and local spatial autocorrelation measures to detect spatial association and identify spatial clusters. Then, I discuss how to explore spatial data via different types of maps and graphics via linking and brushing. The chapter closes with a brief discussion of future directions.

Suggested Citation

  • Ran Wei, 2022. "Exploratory spatial data analysis," Chapters, in: Sergio J. Rey & Rachel S. Franklin (ed.), Handbook of Spatial Analysis in the Social Sciences, chapter 18, pages 305-321, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:19110_18
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