Exploratory Spatial Data Analysis

Sandy Dall'erba, Zhangliang Chen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Exploratory spatial data analysis (ESDA) is an extension of exploratory data analysis as it explicitly focuses on the particular characteristics of geographical data. It is now a well-established geographic information science (GIS)-based technique that allows users to describe and visualize spatial distributions and how they evolve over time, identify atypical locations or spatial outliers, discover patterns of spatial association, clusters, or hot spots, and suggest spatial regimes or other forms of spatial heterogeneity. The strength of ESDA relies on its “data mining” capacity which is particularly useful when no prior theoretical framework exists, as is often the case in multidisciplinary fields of social sciences. It proposes a wide range of largely graphical methods that explore the properties of datasets without the need for formal model building.

Original languageEnglish (US)
Title of host publicationInternational Encyclopedia of Human Geography, Second Edition
PublisherElsevier
Pages357-365
Number of pages9
ISBN (Electronic)9780081022955
ISBN (Print)9780081022962
DOIs
StatePublished - Jan 1 2019

Keywords

  • Choropleth map
  • GIS
  • Geary's c
  • Getis–Ord statistic
  • LISA
  • Moran's I
  • Moran's scatterplot
  • Space-time
  • Spatial autocorrelation
  • Spatial heterogeneity
  • Spatial statistics
  • Spatial weight matrix

ASJC Scopus subject areas

  • General Social Sciences

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