1201 Figure 1 – Study area: The Benkovski tailings storage facility 3. DATASET For this study, a long-term observation window spanning five decades (1975–2025) was defined to encompass the full operational history of the Benkovski 1 and Benkovski 2 tailings facilities. The selection of such an extended time frame enables a comprehensive assessment of their development, operation, and subsequent environmental management over time. A key challenge in the selection of satellite imagery for remote sensing analysis is the presence of cloud cover and the influence of seasonal bias. Clouds interfere with optical sensors, resulting in incomplete datasets and reduced visibility of surface features. Seasonal bias introduces inconsistencies when images acquired at different times of the year are compared without accounting for climatic variability, potentially leading to misleading interpretations that do not accurately reflect annual conditions. To address these limitations, the analysis prioritizes multispectral satellite images with minimal cloud contamination that were consistently acquired during the same period each year. This strategy ensures interannual comparability of vegetation phenology, similar moisture conditions, and allows observed changes to be attributed to actual alterations in the tailings facilities rather than to seasonal fluctuations. June was selected as the primary acquisition period for satellite imagery, as weather conditions during this month are typically stable, with predominantly clear skies and reduced precipitation. This choice maintains phenological consistency throughout the 1975–2025 time series, reduces seasonal bias in vegetation dynamics, and enhances the robustness of multi-temporal change detection. The study utilizes optical multispectral data from the Sentinel-2 and Landsat satellite missions.
RkJQdWJsaXNoZXIy MTM0Mzk2