USE OF GEOPROCESSING AND HISTORICAL PHOTOGRAPHS TO ASSESS THE SUPPRESSION OF VEGETATED AREAS AND SUBSEQUENT INTERPRETATION USING ARTIFICIAL INTELLIGENCE

Abstract

The present study employs geoprocessing techniques, automated interpretation using Artificial Intelligence (AI), and historical aerial images to assess urban expansion and the suppression of vegetated areas in the municipality of Assis (São Paulo State, Brazil) between 1960 and 2025. The images were georeferenced and digitized, generating tables that quantify changes in land use over time. AI was applied to the interpretative analysis of these data, enabling the identification of patterns of urban growth, vegetation fragmentation, and environmental changes across decades. An increase in built-up areas and a progressive reduction in vegetation cover were observed, highlighting anthropogenic pressure on local ecosystems. This approach stands out for its low operational cost, since, after obtaining aerial images—often freely available in public databases—the processing and analysis stages are carried out quickly and efficiently. This characteristic assigns geoprocessing a strategic role in territorial management and sustainable urban planning, allowing public managers to understand urban growth dynamics with precision and agility, supporting environmental and land-use policies. The integration of geoprocessing and Artificial Intelligence proved to be an indispensable tool for monitoring spatial transformations, providing real-time environmental diagnostics, and guiding evidence-based decision-making.

DOI: https://doi.org/10.56238/sevened2025.036-127