Crime Analysis

Module 4 explored using hotspot mapping for crime analysis. We learned how to aggregate crime events to determine crime rates and practiced the use of local and global spatial clustering methods. We also examined spatial patterns in crime rates and socio-economic characteristics. Three hotpot mapping techniques we used were grid based thematic, kernel density, and Local Moran's I. It was determined that the best hotspot mapping technique for police departments to use for predictive policing is kernel density.

The Kernel Density map would be the best map for predicting future homicides because it does more than just consider total households and total homicides or even crime rate. It considers the density of homicides with relation to area and the number of homicides and the output results in smaller, more focused clusters.