Abstract
Urban crime incidents always exhibit a structure of spatio-temporal dependence. Exploration of the spatio-temporal interactions of crime incidents is critical to understanding the occurrence mechanism and spatial transmission characteristics of crime occurrences, therefore facilitating the determination of policing practices. Although previous researches have repeatedly demonstrated that the crime incidents are spatially clustered, the anisotropic characteristics of spatial interaction has not been fully considered and the detailed spatial transmission of crime incidents has rarely been explored. To better understand the spatio-temporal interaction patterns of crime occurrence, this study proposes a new spatial association mining approach to discover significant spatial transmission routes and related high flow regions. First, all near repeat crime pairs are identified based on spatio-temporal proximity. Then, these links between close pairs are simplified by spatial aggregation on spatial grids. Based on that, measures of the spatio-temporal interactions are defined and a spatial association pattern mining approach is developed to discover significant spatial interaction patterns. Finally, the relationship between significant spatial transmission patterns and road network structure is analyzed. The experimental results demonstrate that our approach is able to effectively discover spatial transmission patterns from massive crime incidents data. Our results are expected to provide effective guidance for crime pattern analysis and even crime prevention.
Highlights
Urban crime incidents always exhibit a structure of spatio-temporal dependence
Because crime incidents take the form of events that occur at discrete points in space and time, they are usually modelled by the spatio-temporal point process (STPP)[19]
Spatial interaction patterns are explored based on the proposed method in the "Framework for discovering significant spatial transmission pattern of crime occurrence"
Summary
Urban crime incidents always exhibit a structure of spatio-temporal dependence. Exploration of the spatio-temporal interactions of crime incidents is critical to understanding the occurrence mechanism and spatial transmission characteristics of crime occurrences, facilitating the determination of policing practices. If a crime incident is identified in a given area, the surrounding area may experience an increased risk of similar crime occurrences after a period[4, 10] In this situation, crime incidents exhibit the space–time interaction and the spatial and temporal elements should be considered jointly. The NRC can tell whether there is a significant near repeat victimization pattern in specified spatial and temporal range. Researchers try to examine the extent to which near repeat patterns can prevent c rime[31,32] They found that crime hotspot and near repeat crime are not co-located with each other and significant space–time clustering does not necessarily indicate an actionable near repeat problem. How near repeat phenomena move in space is still a remaining question[34]
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