GIS-Based Spatial Analysis of Crime in a Safe City in the Context of Sustainable Development

The theme of sustainable and safe cities is addressed in the Sustainable Development Goals agenda (SDG 11). The study utilised data on theft incidents from 2018, 2020, and 2023. The aim is to identify theft hotspots in Almaty and to analyse their spatiotemporal distribution and stability using spatial-statistical methods. To assess spatial autocorrelation and its intensity in the spatial distribution, global and local Moran's I (LISA) indices were used in conjunction with kernel density estimation (KDE). The locations of hotspots were identified using the Getis-Ord Gi* (Gi*) method. The temporal analysis revealed that crime varies by month and day. The results show that although the total area of the hot zone expanded between 2018 and 2023, the most intense core of theft became increasingly concentrated within a limited area of the city centre. The spatial distribution of hotspots in Almaty largely corresponded to areas with high human concentration – transport hubs, markets, main streets, and retail shops. One of the potential advantages of studying such crime hotspots is that it helps to prevent crime, reduce city-wide crime levels and contribute to the sustainable and safe development of the city.