Help
Welcome All Technologies Browse by Category

Risk Terrain Modeling Diagnostics Software (RTMDx)

Technology #2012-043

Questions about this technology? Ask a Technology Manager

Download Printable PDF

Image Gallery
Categories
Researchers
Leslie W. Kennedy
Dr. Kennedy is Director of Rutgers Center on Public Security and Professor in the Rutgers University School of Criminal Justice
External Link (rscj.newark.rutgers.edu)
Joel M. Caplan
Dr. Kennedy is Deputy Director of Rutgers Center on Public Security and Associate Professor in the Rutgers University School of Criminal Justice
External Link (rscj.newark.rutgers.edu)
Managed By
David Zimmerrman, PhD
Assistant Director, Licensing 848-932-4046

Researchers at Rutgers who originally developed Risk Terrain Modeling, a methodology for diagnosing spatial crime vulnerabilities, have launched the Risk Terrain Modeling Diagnostics (RTMDx) Utility software.   RTMDx helps to identify and communicate environmental factors associated with specific events. Reports produced can be used to anticipate places where illegal behavior and new crime incidents will emerge and/or cluster. Resources can then be developed for place-based interventions, strategically and tactically allocating resources, and prioritizing efforts to mitigate crime risks.

RTMDx automates most steps of risk terrain modeling using an algorithm to empirically test a variety of spatial influences and analysis increments for every risk factor input to identify the most empirically- and theoretically-grounded spatial associations with known crime incident locations. Then, it selects appropriate risk factors to produce a “Best” risk terrain model.

The final model articulates the vulnerability for crime with relative risk values are assigned to places throughout the study area. The environmental factors that create specific vulnerabilities at places are listed and weighted according to their relative spatial influence on the outcome event. This aids in the prioritization of risk mitigation efforts.

Products Available

The RTMDx software, is available in two versions.

  • Educational version:  A free single end-user license is offered for non-commercial use, educational and short-term trial purposes. Available to students, educators, and agents of some governmental or non-profit organizations. This version does not include output maps.
  • Professional version: Bundled with an RTM Training Webinar, it is a single end-user license for commercial and professional use. This version outputs GeoTiff maps.

Market Applications

  • Map Crime Vulnerabilities 
  • Risk Based Policing
  • Epidemiology
  • Public health
  • National security
  • Transportation/traffic safety
  • Public safety

Advantages

  • Sustainable Predictive Analytics
  • Scalable and Adaptable
  • Valid and Reliable

Awards and Accolades

Won Crime Analyst Award from the International Association of Crime Analysts

Presented at The White House Office of Science and Technology Policy’s second annual “Safety Datapalooza.”

Academy of Criminal Justice Sciences (ACJS) Donal MacNamara Award for Outstanding Journal Publication, 2012

Community Engagement Award for Community Research, Rutgers University-Newark Office of the Chancellor, 2011

Books

  • Lum, C. & Kennedy, L.W. (2011). Evidence Based Counterterrorism Policy. N.Y.: Springer
  • McGloin, J. M. , Sullivan, C.J., & Kennedy,L.W. (2011). When Crime Appears: the Role of Emergence. N.Y.: Routledge
  • Kennedy, L. W. & McGarrell, E. F. (Eds.).(2011). Crime and Terrorism Risk: Studies in Criminology and Criminal Justice. New York:Routledge.
  • Kennedy, L. W. & Van Brunschot, E. (2009),The Risk in Crime. NY: Rowman and Littlefield.
  • Van Brunschot, E. & Kennedy, L. W. (2008). Risk Balance and Security. Thousand Oaks,CA: Sage Publications.
  • Sacco, V. & Kennedy, L. W. (2001). The Criminal Event: Perspectives in Space and Time (2nd Edition). Wadsworth.

Intellectual Property & Development Status

Available through license or distribution agreement

For information about licensing contact:  David Zimmerman