GREEN SPACES AND CRIME: UNDERSTANDING SOCIO-ECONOMIC AND ENVIRONMENTAL INTERACTIONS FOR URBAN SUSTAINABILITY IN SAUDI ARABIA

Abstract

This study investigates the spatial distribution of crime in Saudi Arabia, employing Multiple Linear Regression (MLR) and Geographically Weighted Regression (GWR) models to understand the determinants and patterns of crime across different regions. Utilizing recent data, the analysis focuses on key socio-economic and environmental variables, including green spaces, population density, unemployment rates, income levels, industrial activity, and road infrastructure. The findings reveal significant correlations between these factors and crime rates, highlighting the importance of regional specificity in understanding crime dynamics. The GWR model underscores the spatial heterogeneity in the impact of these variables, with varying strengths and directions of correlations across different administrative regions. This study highlights the need for targeted, region-specific policy interventions and urban planning strategies to effectively mitigate crime. The results also contribute to the broader criminological literature by providing insights into the interplay of socio-economic and environmental factors in shaping crime patterns in a rapidly developing Middle Eastern context. The study concludes with recommendations for future research, emphasizing the importance of incorporating additional variables and employing longitudinal and qualitative approaches to gain a more comprehensive understanding of crime dynamics.