GIS based crime risk analysis and management in cities

For decision makers, crime´s pattern and its risk distribution in space are very important information for crime prevention. In this paper, we investigate crime patterns and hotspots in Beijing with GIS based techniques. The crime locations are projected on the map and their patterns are studied with Nearest Neighbour Index (NNI). The findings showed that crimes are not distributed randomly in space, but clustered as hotspots. Using Kernel density algorithm, the hotspots of the crime in space are identified, and the results are analyzed combined with the environment backcloth. The research in this article demonstrates that GIS could make great contribution to spatial crime risk analysis and prevention management.