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

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