Incorporating Land Cover within Bayesian Journey-to-crime Estimation Models

  •  Joshua Kent    
  •  Michael Leitner    


Crime occurs within asymmetrical landscapes that are occupied by physical and cultural structures that influence
a criminal's behavior in space. These structures manipulate the distribution of available targets and bias the
offender's perceptions of opportunity and target attractiveness. A recent study demonstrated that criminal
geographic profiles can be enhanced to accommodate such ecological characteristics by using land cover
classifications as a proxy for these structures. This study expands on these earlier findings by incorporating land
cover classes within a Bayesian probability framework. Seven traditional and land cover enhanced geographic
profile models for fifty-two burglary, robbery, and larceny serial offenses were compared. Overall, land cover
enhanced models performed significantly better than non-enhanced techniques for measures of search costs
andprobability estimation. Tests measuring a profile's error distance were mixed and failed to confirm
significance between paired comparisons.

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