@article{ref1,
title="Space-time clustering of crime events and neighborhood characteristics in Houston",
journal="Criminal justice review",
year="2015",
author="Zhang, Yan and Zhao, Jihong and Ren, Ling and Hoover, Larry T.",
volume="40",
number="3",
pages="340-360",
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 &quot;super neighborhoods&quot; 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.<p /> <p>Language: en</p>",
language="en",
issn="0734-0168",
doi="10.1177/0734016815573309",
url="http://dx.doi.org/10.1177/0734016815573309"
}