Risk-Based Policing: Evidence-Based Crime Prevention with Big Data and Spatial Analytics

Risk-based policing is the latest advancement in the long history of policing innovations, where research and planning have combined to manage crime risks, prevent crime, and enhance public safety. In Risk-Based Policing, the authors share case studies from different agencies to demonstrate how focusing police resources in risky places, based on smart uses of data and strong analytical work, can address the worst effects of disorder and crime while improving public safety and community relations. Topics include the role of big data; the evolution of modern policing; dealing with high-risk targets; designing, implementing, and evaluating risk-based policing strategies; and the role of multiple stakeholders in risk-based policing. Case studies explore cities such as Colorado Springs, Glendale, Newark, Kansas City, Atlantic City, and others. The book also demonstrates how Risk Terrain Modeling (RTM) can be extended to offer a more comprehensive view of prevention and deterrence.