Modelling long-term land cover changes resulting from mining at Grootegeluk coal mine, Limpopo province, South Africa: implication for environmental management

Abstract Modelling land use and land cover changes resulting from mining at Grootegeluk coal mine has become essential for understanding the spatial and temporal impacts of mining on the surrounding geo-environment and for informing environmental management and rehabilitation strategies. Using Landsat satellite imagery spanning the years 1990, 1999, 2008, 2017, and 2025, the study employs advanced machine learning algorithms, namely eXtreme Gradient Boost (XGB) and Random Forest (RF), to classif