Samenvatting

This article assesses whether the ambient population is a more suitable population-at-risk measure for crime types with mobile targets than residential population. Specifically, the potential use of ambient population as a crime rate denominator and predictor for predictive policing models is evaluated, using mobile phone data (<i>n</i> = 595,858,852 raw data points) as a proxy. The results show that ambient population correlates more strongly with crime than residential population. Crime rates based on ambient population designate different problem areas than crime rates based on residential population. The prediction performance of predictive policing models can be improved by using ambient population instead of residential population. These findings support that ambient population is a more suitable population-at-risk measure, as it better reflects the underlying dynamics in spatiotemporal crime trends.