Spatiotemporal Evolution and Driving Factors of Eco-Environmental Quality in the Shendong Mining Area Based on GEE and Long-Term Landsat Imagery

The Shendong mining area, located in the transition zone between the northern Loess Plateau and the Mu Us Sandy Land, is a representative ecologically fragile region and desert coal base in China. Using Google Earth Engine (GEE) and Landsat imagery from 1999 to 2024, this study constructed a long-term remote sensing ecological index (RSEI) dataset and integrated the Theil–Sen median slope estimator, Mann–Kendall test, and Hurst exponent to examine the spatiotemporal evolution, future trajectories, and multi-stage driving mechanisms of eco-environmental quality (EEQ) at the mining-area and individual-mine scales. At the mining-area scale, RSEI showed pronounced interannual fluctuations and a weak downward trend, characterized by a two-stage, wave-like trajectory with a narrowing amplitude. The mean RSEI and standard deviation decreased from 0.5669 and 0.0855 during 1999–2010 to 0.5182 and 0.0501 during 2011–2024. Moderate and good grades predominated, with lower EEQ in the mining core and higher EEQ in peripheral buffer zones. Across 13 representative mines, ecological quality generally remained moderate but exhibited spatial and stage-dependent heterogeneity, with Liuta Mine showing the greatest variability. Slight degradation was the dominant trend, although local recovery occurred, and Hurst analysis revealed marked spatial differences in future trajectories. RSEI variations in the Shendong mining area exhibited pronounced spatial and stage-dependent associations with high-intensity mining, climatic water–heat conditions, topographic background, and ecological governance and restoration processes. No continuous and irreversible overall decline was observed; however, without an independent non-mining control, the findings represent integrated ecological responses within the mining area rather than causal estimates of mining’s net ecological effect.