NCJ Number
231808
Journal
THE POLICE CHIEF Volume: 77 Issue: 8 Dated: August 2010 Pages: 72-74,76
Date Published
August 2010
Length
4 pages
Annotation
This case study examined how the New Jersey Regional Operations Intelligence Center (NJ ROIC) is applying geospatial statistical modeling to assist local police agencies with reducing violent crime.
Abstract
Geospatial statistical modeling for law enforcement is a methodology based on identifying discernable geospatial preferences associated with a perpetrator's conscious and unconscious activities leading up to criminal behavior, a gang action, or a terrorist threat. The case study presented traces the use of a geospatial statistical modeling tool through one validation test against real crime data from Jersey City, NJ. The NJ ROIC is an "all-crimes, all-threats, all-hazards" fusion center that supports law enforcement and homeland security agencies across New Jersey. Through the governor's Strategy for Safe Streets and Neighborhoods, the NJ ROIC has designed an analytical initiative entitled Project Watchtower. It consists of three core elements: NJ POP (Pins on Paper) focuses on gun violence; NJ TAG (Targeting the Activities of Gangs) targets activities of criminal street gangs; and NJ Trace targets the tracing of crime-related guns entering the State. At regular meetings, the NJ ROIC provides Jersey City police commanders and investigators with intelligence derived from Project Watchtower. Using the December 2008 through March 2009 shooting assessments from NJ POP, NJ ROIC was able to plot the patterns and locations of future shootings for April and May. All but one of the shootings in April and May fell within the projected high-likelihood area. With both strategic and tactical findings, the forecast modeling of likely areas of future shootings based on past shootings seems to be relevant and accurate. This enables commanders to allocate finite resources efficiently and effectively. 7 figures and 2 notes