Over the past decade, a renewed interest in the analysis of crime hot-spots has emerged in the social and behavioral sciences. Spurred by improvements in computing power, data visualization and geographic information systems, numerous innovative approaches have materialized for identifying areas of elevated crime in urban environments. Unfortunately, many hot-spot analysis techniques treat the spatial and temporal aspects of crime as distinct entities, thus ignoring the necessary interaction of space and time to produce criminal opportunities. The purpose of this paper is to explore the utility of statistical measures for identifying and comparing the spatio-temporal footprints of robbery, burglary and assault. Functional and visual comparisons for spatio-temporal clusters are analyzed across a range of space-time values using a comprehensive database of crime events for Cincinnati, Ohio. Empirical results suggest that robbery, burglary and assault have dramatically different spatio-temporal signatures.
- Cluster analysis
- Crime hot spots
ASJC Scopus subject areas
- Pathology and Forensic Medicine