Análise espaçotemporal da dinâmica de roubos de veículos na cidade de São Paulo

Abstract

This study presents an analysis of the spatiotemporal distribution of vehicle thefts in the city of São Paulo, employing data modeling techniques and Geographic Information Systems (GIS), aiming to understand geospatial patterns in crime incidence and apply this information to optimize preventive policing strategies, contextualizing the relevance of spatial analysis in understanding urban crime dynamics by highlighting the ability of this approach to reveal the relationships between urban geography and crime occurrence, with a methodology that includes the collection and processing of large volumes of police occurrence data, analyzed through regional comparisons and the construction of complex networks based on efficiency, degree, and clustering, whose results were evaluated using ANOVA one-way, Kruskal-Wallis, and Dunn tests, delineating high-risk areas compared to other regions, revealing significant differences that highlight specific criminal patterns and variations in vehicle theft dynamics over time, leading to a discussion on the impor- tance of technology and data analysis in modernizing security practices, arguing that the systematic use of spatial and predictive analyses allows for a more informed and proac- tive response to urban crime challenges, providing a scientific basis for decision-making in security and facilitating more precise and well-founded interventions, ultimately highligh- ting the effectiveness of spatial analysis and data modeling as essential tools in modern policing, clarifying the spatial distribution of crimes in São Paulo and demonstrating how this information can be strategically utilized to improve public safety.