Spatial Analysis of Crime in Appalachia: Executive Summary

• NCJ Number: 189560
• Author(s): James G. Cameron
• Date Published: 2001
• Length: 21 pages
• Grant Number(s): 1999-LT-VX-0001
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research)

Annotation

This study aimed to demonstrate the contributions that Geographic Information Systems (GIS) and spatial analysis procedures could make to the study of crime patterns in a largely nonmetropolitan region and examined the extent to which the relationship between various structural factors and crime varied across Appalachia between 1980 and 1990.

Abstract

The research also applied spatial data analysis and confirmatory spatial data analysis procedures to identify patterns of spatial autocorrelation and spatial heterogeneity in the distribution of crime. The research integrated georeferenced data from the Federal Bureau of Investigation Uniform Crime Reports, the Decennial Census of the United States, the Department of Agriculture, and the Appalachian Regional Commission into a GIS database. Results revealed that Appalachia is a region characterized by substantial demographic diversity and socioeconomic change and that a majority of Appalachia’s population continues to live in counties characterized by economic distress and poverty. In addition, crime has been increasing at a faster rate in Appalachia than for the country as a whole. The spatial autocorrelation patterns of both violent crime and property crime indicate that these spatial patterns are not random. These patterns of spatial autocorrelation persist even after controlling for the effects of various structural factors. The spatial autocorrelation patterns for violent crime suggest a possible diffusion process. In addition, different mechanisms may be operating with regard to levels of violent crime and property crime in metropolitan and nonmetropolitan locations. Finally significant subregional differences exist in the effects of various demographic and socioeconomic predictors of crime and in the clustering and spread of crime. Tables, figure, and 15 references