Built environment and Property Crime in Seattle, 1998-2000: A Bayesian Analysis.
Ontology highlight
ABSTRACT: 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 (GIS), 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 proper
SUBMITTER: Matthews SA
PROVIDER: S-EPMC3984884 | biostudies-literature | 2010 Jun
REPOSITORIES: biostudies-literature
ACCESS DATA