Assessing Vegetation Degradation and Thermal Effects of Artisanal Small-Scale Mining Using Remote Sensing Time Series Data

Artisanal and small-scale mining (ASM) has significant environmental implications, including land degradation, deforestation, and thermal ecological changes. However, few studies have systematically quantified the spatiotemporal impacts of ASM on vegetation health and land surface temperature (LST) in sub-Saharan Africa, and none have applied pixel-based transition analysis and regression modeling to capture detailed trends at mining sites. This study addresses this gap by assessing the impacts of ASM from 2012 to 2024 using multitemporal remote sensing data. Vegetation indices such as Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index (GNDVI), Modified Soil-Adjusted Vegetation Index (MSAVI), and Bare Soil Index (BSI), alongside LST data, were derived and analyzed through geospatial techniques and linear regression models. The results indicate significant vegetation degradation over time, with NDVI values at mining sites declining by 61.73% from 2016 to 2024 and similar declines observed in SAVI and GNDVI. BSI values increased significantly, reflecting widespread soil exposure caused by deforestation and mining activities. LST rose markedly, with average temperatures increasing from 22.45°C in 2002 to 27.02°C in 2024, highlighting localized thermal effects due to vegetation loss. Statistical analysis revealed that mining areas experienced the most severe environmental impacts, with linear regression showing negative trends across vegetation indices and increased LST in mining corridors and linear patterns. The study underscores the urgent need for sustainable land management practices and policy interventions to mitigate ASM's environmental impacts. Recommendations include enforcing stricter land reclamation policies, promoting reforestation programs, and adopting geospatial monitoring systems to ensure sustainable resource management. By aligning with Sustainable Development Goals (SDGs) 13, 15, and 12, the findings contribute valuable insights into sustainable environmental conservation strategies for mining-affected regions. © 2025 Elsevier B.V., All rights reserved.