Dynamic Pattern Analysis Framework for cooperative crime prevention

Spatial analysis plays a key role in crime prevention. Traditional approaches such as clustering can find static patterns but do not consider the change of spatial patterns over time. In this paper, we introduce a new analysis framework, dynamic pattern analysis framework (DPA framework) focusing on two types of related dynamic patterns: the displacement or diffusion of spatial patterns over time and the similarity between spatial patterns of different periods. The new framework aims to support cooperative crime prevention in a district of Hong Kong.