309 responses, these indices support the differentiation and interpretation of vegetation, surface water, and other land cover components. When applied to multi-band satellite datasets, spectral indices enable consistent spatial mapping and long-term monitoring of tailings storage facilities, facilitating the detection of surface dynamics, spatial patterns, and temporal changes associated with facility operation and reclamation. For the analysis of the tailings storage facility evolution over the 50-year study period, the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) were selected as the most appropriate and reliable indicators. NDVI (Eq. 1) is extensively used to quantify vegetation presence, vigor, and spatial distribution, making it particularly suitable for identifying reclaimed surfaces, assessing vegetation establishment, and evaluating the effectiveness of progressive rehabilitation measures. NDWI (Eq. 2) is highly responsive to surface water and moisture conditions and allows accurate delineation of decantation ponds, saturated tailings zones, and variations in water extent linked to operational and environmental processes. A key advantage of using NDVI and NDWI lies in their reliance on spectral bands within the visible and near-infrared regions that are consistently available across the Landsat sensor series (MSS, TM, ETM+, and OLI) as well as the Sentinel-2 mission. This spectral continuity enables consistent multi-decadal index calculation and ensures comparability between historical and contemporary satellite observations. The combined use of NDVI and NDWI provides long-term monitoring of vegetation dynamics and water-related processes within tailings facilities, supporting reliable interpretation of spatiotemporal changes over a 50-year period. = − + (1) where NIR = Near-infrared spectral band in satellite images; RED = Red spectral band in satellite images. = − + (2) where NIR = Near-infrared spectral band in satellite images; GREEN = Green spectral band in satellite images. In the context of tailings dam monitoring, photo interpretation refers to the systematic visual examination of satellite imagery to evaluate the condition, structural integrity, and environmental effects of tailings facilities. Satellite data provide a view of large areas and enable the observation of spatial changes and developments around the dam over extended time periods. A key application of photo interpretation is the identification of temporal changes. Through the comparison of recent images with archival datasets, variations in dam morphology, surface characteristics, and surrounding land use can be detected and quantified. Photo interpretation is commonly integrated with complementary data sources, including in situ monitoring measurements, geological and geotechnical information, and GIS, to support the assessment of dam conditions. This integrated approach enhances the reliability of
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