Assessment of the Contribution of Geospatial Technology on Crime Prediction: A Case of Kinondoni, Dar es Salaam

Abstract

Using quantitative methods, this article evaluates the spatial distribution of crime, factors for crime occurrence and crime prediction for the Kinondoni district of Dar es Salaam. The study area and participants were selected using both probability and non-probability sampling techniques. Participatory mapping, remote sensing, document review, GPS survey, and observation were used to acquire data for this study, which examined two types of crimes: burglaries and robberies. Hot spot maps, Kernel density maps, crime patterns, and visualizations were made using ArcGIS software. Areas with a high risk of crime were identified by using kernel density, it was predicted that some areas would have high crime in the future, while other areas would experience low crime. It came clear that Occupation status, Income level and Family breakup are factors for robbery and burglary occurrence where by occupation status has coefficient level of .070, income level has coefficient level of .067 and coefficient level of .878 it remains constant. The spatial distribution of crimes in the Kinondon district is therefore linked to both spatial and spatial elements that cause people to fail in their day-to-day endeavors.