Spatiotemporal Analytics of Urban Population Using Heat Maps
Year: 2025
Type: article
Abstract: Spatiotemporal analytics of population movement and density data plays a crucial role in building a «smart city», providing a basis for optimizing urban planning, improving transport systems, increasing public safety, environmental monitoring, developing digital services and urban analytics. This article presents the results of a study on spatiotemporal patterns of distribution and concentration of the population of Almaty using the method of dynamic heat maps. To build a complete picture of the movement, density and activity of the population, open geographic data from OpenStreetMap (OSM) and aggregated data from a mobile operator were used. Analysis of the load on urban quadrants of 500×500 meters based on OSM made it possible to assess the key patterns of change in population density depending on the time of day. Visualization of spatiotemporal data is implemented using the Python Folium library, which ensured the creation of clear interactive maps. The scientific novelty of the study lies in the study of urban processes in Almaty based on integrated data from different sources reflecting the spatiotemporal features of the dynamics of the urban population. The results obtained demonstrate clear patterns of population concentration that can be used to more accurately forecast and plan the allocation of resources and urban infrastructure.
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408991713