A historical and future impact assessment of mining activities on surface biophysical characteristics change: A remote sensing-based approach

Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate historical impacts mining on surface biophysical characteristics, for first time, predict future in pattern vegetation cover land temperature (LST). In terms utilized data, satellite images Landsat, meteorological data Sungun mine Iran, Athabasca oil sands Canada, Singrauli coalfield India Hambach Germany, used over period 1989–2019. step, spectral bands Landsat employed extract LULC areas based homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was changes. addition, LST maps calculated using single channel algorithm, normalized difference index (NDVI), respectively. second trends NDVI variations different change types time periods investigated. Finally, trend their future. results indicated that forest green space reduced from 9.95 1989 5.9 Km2 2019 mine, 42.14 1999 33.09 sands, 231.46 1996 263.95 2016 coalfield, 180.38 133.99 2017 as result expansion development mineral activities. Our findings about revealed areal coverage will decrease 15% total area by 2039, resulting reduction mean almost 0.06 increase standardized 0.52 0.61 2039. our further indicate (Singrauli mine), values 0.5 (0.44 0.4) 0.38 (0.38, 0.35) (2016, 2017) 0.57 (0.5, 0.47) 0.33 (0.32, 0.28), 2039 (2036, 2035), This can be mainly attributed increasing past well years. discussion conclusions presented interest local planners, policy makers, environmentalists order observe damages brought environment society larger picture.