Spatial Analysis of Crime Distribution in Benin City Using GIS Hotspot Techniques

The spatial analysis of crime patterns is increasingly recognised as a powerful tool for evidence-based policing and urban safety planning. This study analyses the distribution of reported crime incidents in Benin City, Edo State, using Geographic Information Systems and kernel density estimation hotspot techniques. Crime incident data for the period 2021 to 2024 are obtained from the Edo State Police Command and geocoded to street addresses using Google Maps API integration. Five crime categories are analysed, including armed robbery, vehicle theft, burglary, assault, and fraud. Kernel density surfaces are generated for each crime type, and spatial overlay with land use, road network density, and street lighting coverage layers is performed to identify environmental correlates of crime concentration. Results indicate that high-crime hotspots cluster in the Ring Road, Uselu, and New Benin market areas, characterised by high pedestrian traffic, informal commercial activities, and poor street lighting. Residential burglary is notably concentrated in low-income neighbourhoods with unpaved road access. The study demonstrates the practical utility of GIS crime mapping for the Edo State Command and advocates for the institutionalisation of spatially informed patrol deployment strategies. Methodological contributions include an adapted hotspot validation protocol suitable for Nigerian police data quality constraints. Keywords: crime mapping, GIS hotspots, Benin City, kernel density estimation, urban safety.