GLOBAL JOURNAL OF EARTH AND ENVIRONMENTAL SCIENCE
Integrity Research Journals

ISSN: 2636-6002
Model: Open Access/Peer Reviewed
DOI: 10.31248/GJEES
Start Year: 2016
Email: gjees@integrityresjournals.org


Geospatial analysis of crime in Akinyele Local Government Area, Oyo State, Nigeria

https://doi.org/10.31248/GJEES2026.229   |   Article Number: 7DEFFFB34   |   Vol.11 (2) - April 2026

Received Date: 16 January 2026   |   Accepted Date: 25 February 2026  |   Published Date: 30 April 2026

Authors:  Gbemisola Odunola Iyanda and Nathaniel Olugbade Adeoye*

Keywords: spatio-temporal, Dominant, hotspots, policing system, spatial autocorrelation

This study identified and mapped the crime hotspots; determined crime cases and types; and assessed the spatio-temporal dimensions of crimes in Akinyele LGA of Oyo State. This study used primary and secondary data. The primary data were obtained from the structured questionnaire, which was used to sample the opinions of the residents about crime activities and the policing system in the area. The secondary data emanated from the crime records of the Nigeria Police Force (NPF), Oyo State Headquarters, Iyaganku, and Moniya Divisional office. The Police records were used to determine crime hotspots, crime types, and spatio-temporal dimensions of crimes in the study area. The spatial statistical tools (Autocorrelation, Average Nearest Neighbour Analysis and Hotspot Analysis (Getis-Ord Gi*) in ArcGIS 10.8 were used for the analysis of the data. The results showed a total number of 4,501 offences recorded by Nigerian Police over the period of 10 years (2014 – 2023), which were classified into crimes against persons, crimes against property and other offences. The crime hotspots in the study revealed a high concentration in the Moniya and Ojoo axis. The study further revealed that stealing as a crime against property was the highest with (35.84%) in the study area and dominant in the low-density and high-income areas, while assaults as a crime against the person were highest with (39.35%) in the high-density area, such as Moniya and Ojoo and low-income areas such as Olorisaoko, Aroromakinde, Iwokoto, Ikereku Onidundu, Iroko and Olanla. The study concluded that GIS technology was efficient in providing relevant information to the security actors on the effective policing system to combat criminal activities in the study area.

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