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                            Library & Multimedia
 Predicting dynamical crime distribution from environmental and social influences
NCJ Number
              305417

Author(s)
          Simon Garnier;
                        Joel M. Caplan;
                        Leslie W. Kennedy
Date Published

2018
Annotation
              In this paper, the authors investigate the existence of spatio-temporal correlations between successive robbery events, after controlling for environmental influences as estimated by Risk Terrain Modeling (RTM).
Abstract
              Understanding how social and environmental factors contribute to the spatio-temporal distribution of criminal activities is a fundamental question in modern criminology. Thanks to the development of statistical techniques such as Risk Terrain Modeling (RTM), it is possible to evaluate precisely the criminogenic contribution of environmental features to a given location. However, the role of social information in shaping the distribution of criminal acts is largely understudied by the criminological research literature. We begin by showing that a robbery event increases the likelihood of future robberies at and in the neighborhood of its location. This event-dependent influence decreases exponentially with time and as an inverse function of the distance to the original event. We then combine event-dependence and environmental influences in a simulation model to predict robbery patterns at the scale of a large city (Newark, NJ). The authors show that this model significantly improves upon the predictions of RTM alone and of a model taking into account event-dependence only when tested against real data that were not used to calibrate either model. We conclude that combining risk from exposure (past event) and vulnerability (environment), following from the Theory of Risky Places, when modeling crime distribution can improve crime suppression and prevention efforts by providing more accurate forecasting of the most likely locations of criminal events. (Published abstract provided)
      
  
          Additional Details
Grant Number(s)
        2016-IJ-CX-K001


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Next Generation Risk Terrain Modeling Software: Development and Sustainability
    
  
  
Date Published: January 1, 2018
    
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      PatentsRelated Topics
        
                Social and Behavioral Science
        Robbery
        Robbery control programs
        Crime prediction
        Geographic distribution of crime



  
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