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<p>The stability of tailings storage facilities (TSFs) is a critical environmental and safety concern in mining regions, yet site-specific monitoring in West Africa remains limited. This study applied a remote sensing and geospatial analysis framework to assess the environmental and structural stability of the Dokyiwa TSF in Ghana between 2016 and 2024. Using Sentinel-2 imagery, DEM-derived slope gradients, and spectral indices—the Normalized Difference Water Index (NDWI) and Soil-Adjusted Vegetation Index (SAVI)—combined in a weighted overlay analysis, spatial patterns of vegetation loss, surface moisture, and slope steepness were quantified. Results indicate that high-risk zones, characterized by steep slopes (&gt; 15°), sparse vegetation (SAVI &lt; 0.2), and elevated surface moisture (NDWI &gt; 0), dominate the facility, covering 98.27% of the total area. Low-risk zones (1.73%) exhibited gentler slopes, denser vegetation, and balanced moisture conditions, contributing to greater stability. NDWI validation for the 2022 epoch achieved 95% classification accuracy (Kappa = 0.90), confirming the robustness of the approach. The findings highlight escalating risks of erosion, seepage, and potential structural instability, emphasizing the urgent need for targeted interventions, including revegetation, slope re-grading, and improved drainage. This study demonstrates the applicability of integrated remote sensing for proactive TSF stability assessment and provides a replicable framework for guiding environmental monitoring, hazard mitigation, and reclamation planning in tropical mining environments.</p>

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Monitoring of mine tailings ponds in Ghana: a remote sensing-based assessment

  • 期刊论文

  • 发表日期：

    2025年9月28日

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  • Samuel Nana Safo Kantanka,
  • Michael Addaney,
  • Prosper Kpiebaya,
  • Jonas Ayaribilla Akudugu,
  • Enoch Akwasi Kosoe,
  • Joseph Abazaami,
  • Austin Asare

摘要

The stability of tailings storage facilities (TSFs) is a critical environmental and safety concern in mining regions, yet site-specific monitoring in West Africa remains limited. This study applied a remote sensing and geospatial analysis framework to assess the environmental and structural stability of the Dokyiwa TSF in Ghana between 2016 and 2024. Using Sentinel-2 imagery, DEM-derived slope gradients, and spectral indices—the Normalized Difference Water Index (NDWI) and Soil-Adjusted Vegetation Index (SAVI)—combined in a weighted overlay analysis, spatial patterns of vegetation loss, surface moisture, and slope steepness were quantified. Results indicate that high-risk zones, characterized by steep slopes (> 15°), sparse vegetation (SAVI < 0.2), and elevated surface moisture (NDWI > 0), dominate the facility, covering 98.27% of the total area. Low-risk zones (1.73%) exhibited gentler slopes, denser vegetation, and balanced moisture conditions, contributing to greater stability. NDWI validation for the 2022 epoch achieved 95% classification accuracy (Kappa = 0.90), confirming the robustness of the approach. The findings highlight escalating risks of erosion, seepage, and potential structural instability, emphasizing the urgent need for targeted interventions, including revegetation, slope re-grading, and improved drainage. This study demonstrates the applicability of integrated remote sensing for proactive TSF stability assessment and provides a replicable framework for guiding environmental monitoring, hazard mitigation, and reclamation planning in tropical mining environments.