Require Crime Predictive model/tool for hotspot mapping
ABSTARCT :
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 retrospective data to identify the areas of high concentrations of crime and where policing and other crime reduction resources should be deployed. This research uses crime data for a period before a fixed date (that has already passed) to generate hotspot maps, and test their accuracy for predicting where crimes will occur next. Hotspot mapping accuracy is compared in relation to the mapping technique that is used to identify concentrations of crime events (thematic mapping of Census Output Areas, spatial ellipses, grid thematic mapping, and kernel density estimation) and by crime type - four crime types are compared (burglary, street crime, theft from vehicles and theft of vehicles). The results from this research indicate that crime hotspot mapping prediction abilities differ between the different techniques and differ by crime type. Kernel density estimation was the technique that consistently outperformed the others, while street crime hotspot maps were consistently better at predicting where future street crime would occur when compared to results for the hotspot maps of different crime types. The research offers the opportunity to benchmark comparative research of other techniques and other crime types, including comparisons between advanced spatial analysis techniques and prediction mapping methods. Understanding how hotspot mapping can predict spatial patterns of crime and how different mapping methods compare will help to better inform their application in practice.
EXISTING SYSTEM :
? Several general approaches exist in predictive crime mapping, including the use of temporally aggregated hotspots, individual-level analysis of repeat victimization, and various univariate and multivariate analysis of area level data.
? When geocoding at the level of geographic units is not sufficient, several alternatives exist, including street networks, parcels, and address points.
? These jurisdictions were chosen for several reasons, including the availability of existing data, the extent to which GIS is currently being used within these agencies, the size of the agencies, and the depth and breath of information associated with incident-level data.
DISADVANTAGE :
? A key component to tackling crime problems involves the analysis of where crimes take place.
? In order to combat the problems associated with different sizes and shapes of geographical regions, uniform grids (or quadrats) can be drawn in a GIS as a layer over the study area and thematically shaded.
? The KDE technique is currently in vogue, not only because it is the most visually impactive but also because it has the capability of identifying hotspots through a statistically robust methodology.
PROPOSED SYSTEM :
• While many of these techniques serve a somewhat different purpose, they are all concerned with characterizing hotspots in an effort to develop a better understanding of where crimes occur, which can ultimately lead to the design of intervention strategies and the development of prospective crime mapping.
• Hotspot mapping has become a popular analytical technique used by law enforcement, police and crime reduction agencies to visually identify where crime tends to be highest, aiding decision-making that determines where to target and deploy resources.
ADVANTAGE :
? In short, SCA provides law enforcement agencies with the ability to provide more effective and efficient service to the community.
? Several approaches have been developed recently to assess the performance of hotspot analysis techniques for crime prediction, including the Prediction Accuracy Index (PAI) and the Recapture Rate Index (RRI).
? Hotspots appeared relatively robust, although this can partially be attributed to the large bandwidth used (500 meters).
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