Built environment and property crime in Seattle, 1998-2000: A Bayesian analysis

Stephen A. Matthews, Tse Chuan Yang, Karen L. Hayslett, R. Barry Ruback

Research output: Contribution to journalArticlepeer-review


The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems, spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998-2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary.

Original languageEnglish (US)
Pages (from-to)1403-1420
Number of pages18
JournalEnvironment and Planning A
Issue number6
StatePublished - 2010
Externally publishedYes

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Environmental Science (miscellaneous)


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