Investigating the Influence of Land Use and Alcohol Outlet Density on Crime in Juja Sub-County, Kenya

Abstract

The main objective of this study was to investigate the linkage between land use and alcohol outlet density and crime in Juja sub-county, Kenya. Crime data ( n = 1560) was obtained from the Juja Police Station for the years 2017, 2019, 2020, and 2021. Land use land cover classification of our study area was performed to obtain land use classes (commercial, agricultural, forest, grassland, industrial, residential, and waterbody), and zonal operations at the zone level ( n = 233) were performed to obtain summary values of each land use type per zone. Alcohol outlet density was also calculated at the zonal level. Population was identified as a crime determinant factor in addition to land use and alcohol outlet density. From these factors, the 4 most significant ones (residential, agricultural, population, and off-premise outlet density) were identified using ordinary least squares (OLS) model. This revealed that off-premise alcohol outlet density had a statistically significant negative relationship with crime, while residential areas had the highest statistically significant positive relationship with crime. While on-premise alcohol outlet density did demonstrate the highest positive coefficient with crime, this relationship was not statistically significant. This infers that while on-premise alcohol outlet density may explain crime in areas where such establishments are dense, with high crime rates, they may not explain crime in other areas of the sub-county that equally recorded high-density crime rates. The random forest algorithm was then adopted to predict crime from the most significant variables.

Wemap‐based direction model for individuals with limited spatial orientation skills

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“…To meet the demands of map enthusiasts/users who want to participate in deciding map content (Lan et al., 2022), some platforms have been developed, such as OpenStreetMap (Haklay & Weber, 2008; Mburu & Mutua, 2023), People's Map (https://thepeoplesmap.net/), and Tagzania (https://www.codesyntax.com/en/projects/tagzania.com). Such platforms leverage crowdsourcing techniques to gather geospatial data from voluntary users who are geographically dispersed worldwide to create maps.…”