Risk Clusters, Hotspots, and Spatial Intelligence: Risk Terrain Modeling as an Algorithm for Police Resource Allocation Strategies

Abstract

The study reported here follows the suggestion by Caplan et al. (Justice Q, 2010) that risk terrain modeling (RTM) be developed by doing more work to elaborate, operationalize, and test variables that would provide added value to its application in police operations. Building on the ideas presented by Caplan et al., we address three important issues related to RTM that sets it apart from current approaches to spatial crime analysis. First, we address the selection criteria used in determining which risk layers to include in risk terrain models. Second, we compare the ''best model'' risk terrain derived from our analysis to the traditional hotspot density mapping technique by considering both the statistical power and overall usefulness of each approach. Third, we test for ''risk clusters'' in risk terrain maps to determine how they can be used to target police resources in a way that improves upon the current practice of using density maps of past crime in determining future locations of crime occurrence. This paper concludes with an in depth exploration of how one might develop strategies for incorporating risk terrains into police decisionmaking. RTM can be developed to the point where it may be more readily adopted by police crime analysts and enable police to be more effectively proactive and identify areas with the greatest probability of becoming locations for crime in the future. The targeting of police interventions that emerges would be based on a sound understanding of geographic attributes and qualities of space that connect to crime outcomes and would not be the result of identifying individuals from specific groups or characteristics of people as likely candidates for crime, a tactic that has led police agencies to be accused of profiling. In addition, place-based interventions may offer a more efficient method of impacting crime than efforts focused on individuals.

Bus Stops and Violence, Are Risky Places Really Risky?

“…The risk factors are often determined and/or weighted based on a regression or some other technique to ascertain how important they are for the crime outcome to be studied, and the resulting map of a city thus shows the relative risk for crime in each of the cells the city has been divided into. RTM has been tested on different crimes, including gun violence Kennedy et al 2011), gun crime , assault , burglary (Moreto et al 2013), violence against the police (Caplan et al 2014b), and motor vehicle theft .…”

Risk terrain modeling for monitoring illicit drugs markets across Bogota, Colombia

“…Previous studies have demonstrated that drug dealing locations tend to cluster, especially in large cities (Rengert et al 2000;Kennedy et al 2011). Nevertheless, in Bogota, these concentrations of illicit drugs sale points are increasingly combined with a constellation of scattered sale points located in peripheral areas of the city.…”

Predicting Dynamical Crime Distribution From Environmental and Social Influences

“…Figure 3 shows examples of forecasting landscapes produced for January [1][2][3][4][5][6][7]2012, for the RTM-only model (Figure 3A), the event-dependence-only model (Figure 3B), and the full model (Figure 3C), against the actual robbery occurrences during that period (white dots). Figure 3D shows for that particular week in 2012 how each model compares to the random model following the procedure described in section Model Performance.…”

“…More recently, Caplan and Kennedy [4] proposed Risk Terrain Modeling (RTM) as a spatial analytical technique for empirical study of crime distribution. Resulting risk terrain maps show where certain crime events are statistically more likely to occur based on certain environmental vulnerabilities at micro places [4][5][6][7]. This technique considers the effects of multiple factors on creating distinct, identifiable areas that are conducive to crime, but emphasizes the importance of environmental characteristics on the attraction of motivated offenders and the emergence, persistence, and desistance of crime [4][5][6].…”