Welcome to the InfoSci Platform
Reference Hub10
Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery

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

Elizabeth Groff
Copyright: © 2008 |Pages: 26
ISBN13: 9781599045917|ISBN10: 1599045915|EISBN13: 9781599045931
DOI: 10.4018/978-1-59904-591-7.ch012
Cite Chapter Cite Chapter

MLA

Groff, Elizabeth. "Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery." Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems, edited by Lin Liu and John Eck, IGI Global, 2008, pp. 226-251. https://doi.org/10.4018/978-1-59904-591-7.ch012

APA

Groff, E. (2008). Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery. In L. Liu & J. Eck (Eds.), Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems (pp. 226-251). IGI Global. https://doi.org/10.4018/978-1-59904-591-7.ch012

Chicago

Groff, Elizabeth. "Characterizing the Spatio-Temporal Aspects of Routine Activities and the Geographic Distribution of Street Robbery." In Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems, edited by Lin Liu and John Eck, 226-251. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-591-7.ch012

Export Reference

Mendeley
Favorite

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.