Predicting residential burglaries based on building elements and offender behavior: Study of a row house area in Seoul, Korea

Authored by Yoonseok Hwang, Sungwon Jung, Jaewook Lee, Yongwook Jeong

Date Published: 2017

DOI: 10.1016/j.compenvurbsys.2016.09.004

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Current methods for predicting residential burglaries mostly rely on analyses of crime patterns based on a real information. While this model is valid on an urban scale, it fails to consider street-scale environmental factors as well as offender behaviors in response to those factors. To improve the predictability of crime-simulation studies, this study investigated two influential factors in the occurrence of residential burglary: the physical properties of building elements and offender behaviors in response to those properties. First, a prediction algorithm was designed based on analyses of the factors. Next, a prediction method was established by modeling a virtual 3-D environment and a virtual offender using the algorithm. Lastly, the probability of residential burglary was analyzed via a simulation using the prediction method. A comparison of the simulation results with actual residential burglary data confirmed that the proposed method has statistically significant predictability. (C) 2016 Published by Elsevier Ltd.

Tags

Simulation patterns environmental design opportunity Residential burglary Virtual agent-based modeling Crime prediction Offender behavior Crime-prevention