An analysis of crime hot spots using GPS tracking data of children and agent-based simulation modeling

Abstract

Although the problem of a lack of an adequate denominator of crime rates has been widely recognized, relatively few solutions have been found. This paper proposes a sophisticated method of analyzing crime hot spots using global positioning system (GPS) tracking data and agent-based simulation modeling. The goal of the proposed analysis technique is to estimate a population at risk across time and space at the micro-level, such as streets and locations (e.g. parks and playgrounds). In order to create valid estimates of a population at risk and to illustrate how the estimated population at risk can be used in crime analysis, this paper presents a series of three sub-studies. First, GPS tracking data were obtained for two weeks for 80 children in the second and fifth grades from one school located in a suburb of Tokyo, Japan. GIS software was used to analyze the GPS data in order to identify streets and places that the children frequented. Second, agent-based simulation modeling was developed to extend the proposed analysis method to school districts that had not participated in the GPS sub-study. In the process of developing a simulation algorithm, the validity of simulation modeling was checked by comparing the simulation results with the GPS tracking data. Third, victimization surveys with maps were conducted in six schools (including the school that participated in the GPS sub-study) that identified locations of crime incidents. Victimization survey results were overlaid with the analysis results of GPS data and agent-based simulation modeling in order to examine crime hot spots. The proposed technique of agent-based modeling produces an accurate denominator of crime rates at the micro-level which can then be used to analyze crime hot spots properly. In particular, this paper discusses how crime analysts can identify different types of hot spots, such as crime generators and crime attractors, by examining the number of crime incidents and the magnitude of crime rate. This paper argues intervention strategies need to be tailored for each type of crime hot spots, as these crime hot spots develop through different mechanisms. Finally, this paper discusses limitations of the proposed technique and the direction of future research.