Certain investigations on the spatial temporal crime hotspot for identifying the crime activities by using spatial cluster method

Abstract

Hotspot mapping is a popular analytical technique that is used to help identify where to target police and crime reduction resources In essence hotspot mapping is used as a basic form of crime prediction relying on data to identify the areas of high concentrations of crime and where policing and other crime reduction resources should be deployed A number of different mapping techniques are used for identifying hotspots of crime point mapping thematic mapping of geographic areas spatial ellipses grid thematic mapping and Kernel Density Estimation This research develops temporal clustering for crime events and applies spatial clustering for each temporal cluster created to provide crime related hotspots based on space and time and implementing spatial clustering simulation based on analysis of spatial temporal hotspot for predicting crime activities is achieved using crime data which provides strong aggregation between various crime data attributes and analyzes the time and space relationship with repeat and near repeat victimization of crime activities The Spatial clustering algorithm based on CLIQUE Optimization algorithm to find the exact hotspot in the kernel density estimation map Spatial data space is divided by hyper planes which are entertained with axis paralleled histogram in the CLIQUE Optimization algorithm A division of data space relies on the natural distributing character of input data space to improve the accuracy and efficiency of spatial clustering