Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery

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Author(s): Elizabeth Groff (Temple University and Institute for Law and Justice, USA)
Copyright: 2008
Pages: 26
Source title: Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems
Source Author(s)/Editor(s): Lin Liu (University of Cincinnati, USA)and John Eck (University of Cincinnati, USA)
DOI: 10.4018/978-1-59904-591-7.ch012

Keywords: Digital Crime & Forensics / Information Science Reference / IT Security and Ethics / Security & Forensics

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Abstract

It is widely recognized that the spatio-temporal components of human behavior strongly influence where and when people converge in space and time. Routine activity theory (Cohen & Felson 1979) ties the frequency of convergence to crime rates. This chapter builds on an earlier agent-based model (Groff, in press-a) by drawing on geographic theory to develop two additional versions of the model in which the agents have more fully developed activity schedules. A series of experiments are conducted which compare the spatial pattern of street robbery events from the original version of the model to the two new versions and to the empirical distribution of street robberies in Seattle, WA. The findings indicate temporally and spatially defined activity spaces have a significant impact on the spatial pattern of crime events produced by the model. The version with spatio-temporal activity spaces produces patterns most like the empirical distribution of street robberies.

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Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery

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