Dr. Timothy C. Hart,Dr. Gabriel R. PaezDr. Chivon H. FitchCoates, Kehara2022-11-112022-11-112022-12http://hdl.handle.net/20.500.11868/3671Kernel density estimation (KDE) is one of the most popular crime hot spot mapping methods used to reduce and prevent crime. However, this technique does not consider where crime cannot occur within a study area when a crime risk surface is interpolated. Therefore, a knowledge gap exists as to how effective incorporating barriers into KDE analysis can be in producing more accurate prospective crime hot spot maps. Therefore, the current study investigated whether the predictive accuracy of crime forecasts based on KDE will improve when barriers to crime are incorporated into the analytic process.en-USBarriersKernel Density EstimationPredictive PolicingCrime AnalysisThesis