A spatiotemporal analysis of crimes reported in the North Shewa Zone of Amhara region, Ethiopia

Abstract

Crime is a societal problem that has an impact on the quality of life and economic prosperity of a society. So, crime data analysis is used to understand more about how and why crime happens, as well as the policy measures to reduce its rate. Thus, this study focused on a spatiotemporal analysis of crimes perpetrated in North Shewa Zone between September 2018 and August 2020. The crime data were collected using files from the North Shewa Zone Police office for each district during the years in question to evaluate it. The spatial shapefiles were then geocoded and non-spatially connected using Google Maps to produce the geographic coordinates latitude and longitude. Cluster sampling technique was used to determine the number of districts included in the study. The Moran’s I and Gertis-Ord methods were used. The Moran’s I statistics for crimes from September 2018 to August 2019 and September 2019 to August 2020 were 0.079 (Z-score = 3.685; p = 0.000228), and 0.0482 (Z-score = 2.567; p = 0.010248), respectively. In both years, there was a clustered distribution of crimes, or there was spatial dependence among places. Similarly, Getis-Ord Gi* indicated that in several of the analyzed districts, the majority of the study wards had statistically significant crime hotspots.

Keywords

• crime
• cluster sampling
• gis
• hotspots
• spatial autocorrelation