Remote Sensing and Spatial Statistics as Tools in Crime Analysis
Dongmei Chen (Queen’s University, Canada), John R. Weeks (San Diego State University, USA) and John V. Kaiser Jr. (San Diego State University, USA)
Copyright: © 2005
This chapter explores the feasibility and utility of using aerial photography or remotely sensed satellite imagery to identify geographic or “place” features that may be associated with criminal activity. It assesses whether or not variables derived from satellite images can provide surrogate relationships between land use and crime. A review of the remote sensing literature suggests two basic approaches to the use of remotely sensed images in law enforcement: (1) tactical; and (2) analytical. The tactical approach uses the imagery as a background to the maps and other spatial information that an officer on the beat might have as he or she is investigating a crime or emergency situation. The analytical approach uses the remotely sensed images to create new variables that may serve as proxies for the risk of crime in particular locations. In this study we employ the analytical approach to the use of remotely sensed images, classifying images according to the presence or absence of vegetation within a pixel, as well as the classification of specific urban attributes, such as parking lots. We also employ spatial statistics to quantify the relationship between features of the images and crime events on the ground, and these analyses may be particularly useful as input to policy decisions about policing within the community.