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Crime Hotspot Analysis using CrimeStat Grant Buhay Introduction The concept of Geographical Information Systems and profiling is not new to the area of Community Policing Mechanical methods of point pattern analysis and data separation have been benefiting society ever since Dr Snows landmark discovery of the tainted well Waters 1995 The analysis of spatial and temporal data has been critical to the successes of many criminal investigations Buzzwords such as geographic criminal and psychological profiling have rejuvenated an interest in analytical geography and the advances in computer technology have given geographers a medium in which to express the capabilities of their science Waters 1999 Rossmo K httptpwwwecricanadacomAboutECRIhtm Criminal Geographic Targeting is an example of the practical application of academic research concludes Rossmo and is finally putting geographers on the map Rossmo 1997 The purpose of this paper is to explore the spatial statistics program for the analysis of crime incident locations CrimeStat which has been developed by Ned Levine PhD and Associates under a grant from the National Institute of Justice In particular the hotspot analysis module which include the K-means clustering nearest neighbor hierarchical spatial clustering and Local Moran statistics will be examined for their functionality ease of navigation and interpretability of results The K-Means analysis will be employed to make the determination of whether the distribution of data points display a clustered pattern or one of complete spatial randomness One would expect the hotspot aspect of the module to highlight areas of high concentration that may not be apparent on maps that simply plot crime locations It is in this area of hotspot identification and analysis that this paper will focus Literature Review A hot spot has been defined as a condition indicating some form of clustering in a spatial distribution However not all clusters are hot spots because the environments that help
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