The article demonstrates the use of remote sensing and spatial analysis methods in ArcGIS to detect land cover changes in the suburban area of Ivano-Frankivsk over 20 years (from 2004 to 2024). The main materials for the study were Landsat 5, Landsat 8, and Sentinel-2 satellite images. These data made it possible to analyze changes in land use and landscapes using geoinformation methods. Six land classes were identified using the maximum likelihood method: built-up areas, forests, water bodies, agricultural land, pastures, and open land. The symmetric difference operation was used to detect changes in development over different periods. The expansion of built-up areas and changes in the nature of land use in the suburban area were confirmed using remote sensing data. The areas with the most intensive growth of development are identified: villages within a 5-km radius within the Ivano-Frankivsk city community. The obtained results confirm the relevance of further research on suburbanization processes and the need to develop effective spatial development management strategies, considering the environmental impact of human activity.
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