310 interpretations and improves the understanding of potential risks and environmental impacts. As a result, photo interpretation serves as an effective method for visually assessing dam performance, identifying anomalies, and supporting environmental impact evaluation. When used in conjunction with other monitoring techniques and expert analysis, it contributes significantly to the safe operation and sustainable management of tailings dams. Geographic Information Systems (GIS) are an essential component of tailings dam monitoring, providing advanced capabilities for the storage, analysis, and visualization of spatially referenced data. GIS enables the integration of diverse datasets, such as topographic information, geological layers, satellite imagery, and unmanned aerial vehicle (UAV) data, within a unified analytical framework. In addition, GIS facilitates the management and analysis of historical records related to dam operation, maintenance activities, and inspection results. This temporal perspective supports the assessment of long-term performance, the identification of trends, and the evaluation of dam stability. 5. RESULTS AND ANALYSES As a result of the processing workflow illustrated in Figure 2, all 51 satellite images (Table 1) from the 1975–2025 time series were processed. 5.1 Normalized Difference Vegetation Index (NDVI) Higher NDVI values (dark green) indicate increased vegetation cover and improved surface stabilization, whereas low or negative NDVI values (light green) are consistently associated with barren tailings surfaces or areas undergoing active deposition. In the present study, this index was used to systematically monitor and outline spatiotemporal changes in
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