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Journey-to-Crime Estimation (CrimeStat IV: A Spatial Statistics Program for the Analysis of Crime Incident Locations, Version 4.0)

NCJ Number
Date Published
June 2013
102 pages

This is the fourth of five chapters on "Spatial Modeling I" from the user manual for CrimeStat IV, a spatial statistics package that can analyze crime incident location data.


This chapter, "Journey-to-Crime Estimation," presents CrimeStat's journey-to-crime routine, which is a distance-based method that estimates the likely residential location of a serial offender. It involves an application of "location theory," a framework for identifying optimal locations from a distribution of markets, supply characteristics, prices, and events. Following an explanation of location theory, the chapter discusses a sub-set of location theory that models the travel behavior of individuals, i.e., the "gravity function," which is an application of Newton's fundamental law of attraction (Oppenheim, 1980). Related discussions pertain to the social applications of the "gravity" concept, intervening opportunities, urban transportation modeling, and alternative distance decay functions. Other issues addressed prior to explaining the detail of CrimeStat's journey-to-crime routine are the travel behavior of criminals and prediction of the location of serial offenders. Major sections of the description of CrimeStat's journey-to-crime routine discuss journey-to-crime estimation using mathematical functions; empirically estimating a journey-to-crime calibration function, journey-to-crime estimation using a calibrated file, and the accuracy of the methods. Also described in the journey-to-crime module is a utility that can help the user visualize the pattern before selecting a particular estimation model. This is a Draw Crime Trips routine that draws lines between the origin and destination of individual crime trips. Seven attachments by various authors provide examples and supplementary information pertinent to the application of CrimeStat's journey-to-crime routine. 104 references and extensive data tables and figures

Date Published: June 1, 2013