Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Risk terrain modeling : crime prediction and risk reduction
Caplan J., Kennedy L., University of California Press, Berkeley, CA, 2016. 192 pp. Type: Book (978-0-520282-93-3)
Date Reviewed: Nov 29 2016

Geospatial forecasting (predicting where and when in the future to find entities and events of interest) is a rich area of research with numerous important applications, including environmental management, antiterrorism, and predictive policing. Caplan and Kennedy, at the Rutgers Center for Public Security, have developed an approach they call “Risk Terrain Modeling” (RTM), with primary focus on supporting law enforcement. This volume summarizes their approach, which is supported by free software available from Rutgers.

The fundamental assertion of RTM is that some places pose a higher risk of crime than others, and this risk can be decomposed into three factors: vulnerability (environmental features that attract criminal activity), global exposure (areas with high concentrations of criminal activity), and local exposure (sequences of crime events within a short period of time). The RTM toolset allows users to define these factors, calibrate them against historical data, and generate risk maps that can guide police activity. The book includes case studies drawn from several US cities.

Chapter 1 argues for a context-driven analysis of risk. Chapter 2 introduces a step-by-step methodology for doing RTM and includes an interesting analysis of criteria for a successful forecast. This problem is not as simple as measuring accuracy because an important use of forecasts is to deploy police resources, which should have the effect of suppressing the events being forecast. Instead, the proposed criteria focus on the nature of the data, the ability of the results to be deployed and explained, and their face validity. Chapters 3 through 5 develop the theory of RTM, built around the three factors of vulnerability, global exposure, and local exposure. Chapter 6 discusses how specific events interact with risky places, while chapter 7 describes a framework for applying RTM in operations and chapter 8 explores how the RTM theory guides risk reduction activities. The book includes a glossary, a bibliography through 2015, and an index.

This volume will provide useful background on a system that is making useful, concrete contributions to public safety in a number of jurisdictions. However, given its academic provenance, one is surprised that it does not offer a systematic comparison of the benefits of RTM with respect to other similar efforts, both academic and commercial. Academic researchers addressing similar problems include Brown at the University of Virginia; Shekhar at the University of Minnesota; Rossmo at Texas State University; and de Smith, Longley (both at University College London), and Goodchild (UC Santa Barbara), authors of a leading textbook on all aspects of geospatial analysis [1], to name only a few of the more prominent members of the community. In addition, several commercial products dealing with the same problem are widely used in practice, including Ned Levine’s Crimestat program, the ArcGIS Spatial Analyst Toolbox, and IBM’s SPSS. The last two are more development environments than finished tools, but Crimestat would appear to be a direct competitor with RTM, embodying a much wider array of methods that include some of those in RTM. Caplan and Kennedy do not discuss any of these efforts.

This volume will be useful for criminologists and social scientists interested in the theoretical background of the RTM system.

Reviewer:  H. Van Dyke Parunak Review #: CR144949 (1702-0107)
1) de Smith, M. J.; Goodchild, M. F.; Longley, P. A. Geospatial analysis: a comprehensive guide to principles, techniques and software tools (3rd ed.). Troubador, Leicester, UK, 2009.
Bookmark and Share
  Featured Reviewer  
 
Model Development (I.6.5 )
 
 
Spatial Databases And GIS (H.2.8 ... )
 
 
Model Validation And Analysis (I.6.4 )
 
 
Information Systems Applications (H.4 )
 
Would you recommend this review?
yes
no
Other reviews under "Model Development": Date
Toward a logical/physical theory of spreadsheet modeling
Isakowitz T., Schocken S., Henry C J. ACM Transactions on Information Systems 13(1): 1-37, 1995. Type: Article
Jun 1 1996
Model-Based Diagnosis or Reasoning from First Principles
Peischl B., Wotawa F. IEEE Intelligent Systems & Their Applications 18(3): 32-37, 2003. Type: Article
Nov 6 2003
Simulation modeling handbook: a practical approach
Chung C., CRC Press, Inc., Boca Raton, FL, 2003.  608, Type: Book (9780849312410)
Nov 26 2003
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy