Using exploratory spatial data analysis to leverage social indicator databases: The discovery of interesting patterns

Luc Anselin, Sanjeev Sridharan, Susan Gholston

Research output: Contribution to journalArticle

90 Scopus citations

Abstract

With the proliferation of social indicator databases, the need for powerful techniques to study patterns of change has grown. In this paper, the utility of spatial data analytical methods such as exploratory spatial data analysis (ESDA) is suggested as a means to leverage the information contained in social indicator databases. The principles underlying ESDA are illustrated using a study of clusters and outliers based on data for a child risk scale computed for countries in the state of Virginia. Evidence of spatial clusters of high child risks is obtained along the Southern region of Virginia. The utility of spatial methods for state agencies in monitoring social indicators at various localities is discussed. A six-step framework that integrates spatial analysis of key indicators within a monitoring framework is presented; we argue that such a framework could be useful in enhancing communication between State and local planners.

Original languageEnglish (US)
Pages (from-to)287-309
Number of pages23
JournalSocial Indicators Research
Volume82
Issue number2
DOIs
StatePublished - Jun 1 2007

Keywords

  • Community Health Indicators
  • Global association
  • Local association
  • Spatial analysis
  • State-level planning

ASJC Scopus subject areas

  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Sociology and Political Science
  • Social Sciences(all)

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