Crime mapping and hot spot analysis using geospatial data in Jalingo metropolis of Taraba State, Nigeria

Abstract

Crime mapping and hot spot analysis are topical and significant research across the fields of criminology, data digging, city planning and law enforcement for crime control. This study seeks to identify high crime areas which require an officer presence and predicting the possible response demand to increase the efficiency of response officer patrols. Crime type and patterns exist on a spatial level; these patterns and type can be grouped geographically by physical location, and analyzed contextually based on the region in which crime occurs. The study aimed at analyzing crime hotspots using geospatial data in Jalingo metropolis by identifying the different kinds of crime in the study area, determine the spatio-temporal variation of crime occurrences in the study area and determine the high crime density area (hotspot).This study proposed a method to identifying level crime, localize crime hotspots, identify relationship between spatiotemporal crime patterns and social trends, and analyze the resulting data for the purposes of knowledge discovery and anomaly detection. Several types of crime were analyzed in this dataset, including burglary, bribery, forgery ,murder ,rape ,theft drug abuse, assault, and robbery analysis, several interesting findings were drawn about crime in Jalingo metropolis, including: Crime mapping and hotspots with steadily increasing crime levels, hotspots with unstable crime levels, synchronous changes in crime trends throughout Jalingo metropolis as a whole, individual months in which certain hotspots behaved anomalously, and a strong relationship between crime hotspot locations. This type of statistical and correlative analysis of crime patterns will help law enforcement agencies predict criminal activity, allocate resources, and promote community awareness to reduce overall crime rates in Jalingo metropolis. Policing approaches like patrolling and response to crime incidents can be more effective if proper crime mapping and crime hot spot analysis data are available for policing is used to make decisions on crime control in the study area. Predictive policing in crime management use information such as historical crime data to predict crime patterns and response demand. Historical crime data is used to identify high crime areas through kernel density estimation. It is also used to anticipate the levels of response demand. Both of these factors are used to determine how to direct police patrols. This study revealed how kernel density estimation is used for crime mapping and hot spot.