Journal of Geographic Information System

Volume 15, Issue 4 (August 2023)

ISSN Print: 2151-1950   ISSN Online: 2151-1969

Google-based Impact Factor: 1.07  Citations  h5-index & Ranking

Spatial Pattern and Distribution of Crime in Suleja Lga, Niger State, Nigeria

HTML  XML Download Download as PDF (Size: 13311KB)  PP. 379-390  
DOI: 10.4236/jgis.2023.154019    138 Downloads   767 Views  

ABSTRACT

The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.

Share and Cite:

Ocholi, I. , Abuh, P. , Samuel, A. and Musa, A. (2023) Spatial Pattern and Distribution of Crime in Suleja Lga, Niger State, Nigeria. Journal of Geographic Information System, 15, 379-390. doi: 10.4236/jgis.2023.154019.

Cited by

No relevant information.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.