Citation

Zhang Y, Zhao J, Ren L, Hoover LT. Crim. Justice Rev. 2015; 40(3): 340-360.

Copyright

(Copyright © 2015, Georgia State University Public and Urban Affairs, Publisher SAGE Publishing)

DOI

10.1177/0734016815573309

PMID

unavailable

Abstract

Spatial-temporal interaction analysis is employed to identify repeat and near-repeat patterns of crime in time and space. Most research to date addresses burglary and shooting incidents. Using the Knox method for space-time interaction, this study analyzes crime data in 12 "super neighborhoods" located in Houston's crime-heavy southwest quadrant to explore spatial-temporal clustering of three types of crime, namely, residential burglary, street robbery, and aggravated assault. The findings suggest that each type of crime event has a unique clustering signature. Residential burglaries show significant space-time clustering in a relatively longer time range (up to 90 days) and distance interval (up to 1.55 miles). In contrast, street robberies present significant clustering only up to 6 days and a quarter of a mile. For aggravated assault, the clusters of pairs occur within the interval of 7 days and within a little more than 1 mile of an initial assault. Examination of the socioeconomic characteristics of the neighborhoods indicates that crime events cluster more often in low income and racially/ethnically diverse neighborhoods. Significant spatial correlations of crime clusters are detected. The findings offer insight into potential suppression of crime events that are time and space correlated.

Language: en