Evaluation of crime pattern in Khanna local government using geographic information system

Abstract

Sustainable development can only take place in an atmosphere of peace and tranquility. The state of insecurity in Rivers State and Nigeria at large has been on the rise over the past decade. The Nigerian security agencies have not been able to effectively tackle and nib crime activities in the bud. This has led to the loss of lives, businesses, and other attendant socio-economic effects. The distribution of crime across the landscape is geographically random since crime is a human phenomenon, hence geography plays an important role in law enforcement and criminal justice. Geographic information system (GIS) can help the security agency in tactical planning and response; allocating resources quickly and more effectively, determine mitigation priorities, analyze historical events, and predict future trends and patterns. The main aim of this paper is crime modeling and analysis using the Geo-information system. This paper uses GIS to visualize, analyze, and explain criminal activities within Khanna local government in a spatial context. To achieve this, crime data and records covering over seven years were obtained from the Nigerian Police Force in Bori. Supplementary and attribute data were collected through fieldwork using the Global Positioning System (GPS) to provide the coordinates of crime points and scenes in the local government and other associated data. A spatial database was created using ArcGIS software. The crime hotspot map and crime density map of the study area was produced using the ArcGIS pro tool- Gi-Bin fixed 234-FDR at 99%,95%, and 90% confidence level respectively for the hot spots and cold spots respectively. The maps and results from the spatial analysis performed can help the police to carry out patterns and trends analysis across multiple jurisdictions; enlist community action, enhancing implementation of various policies to reduce crime in the study area. It can also provide tools and techniques to capture, forecast future crime occurrence in the area and reduce crime incidences.