Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

ABSTRACT: A key issue in the spatial and temporal analysis of residential burglary is the choice of scale: spatial patterns might differ appreciably for different time periods and vary across geographic units of analysis. Based on point pattern analysis of burglary incidents in Columbus, Ohio during a 9-year period, this study develops an empirical framework to identify a useful spatial scale and its dependence on temporal aggregation. Our analysis reveals that residential burglary in Columbus clusters at a characteristic scale of 2.2 km. An ANOVA test shows no significant impact of temporal aggregation on spatial scale of clustering. This study demonstrates the value of point pattern analysis in identifying a scale for the analysis of crime patterns. Furthermore, the characteristic scale of cluster

SUBMITTER: Alazawi M 

PROVIDER: S-EPMC8884495 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature