Abstract: Open-pit coal mines are widely distributed in China, and the ecological monitoring of which is susceptible to geographical heterogeneity in hydrothermal conditions, vegetation types, and soil characteristics. To achieve accurate cross-regional monitoring, it is essential to evaluate the applicability of ecological quality assessment indices. Based on Google Earth Engine and uniform Landsat 8 OLI data, we used the standardized remote sensing ecological index (RSEIs), land surface ecological status composition index (LSESCI), new remote sensing-based ecological index (RSEInew), and surface coal mine ecological index (SurMEI) to evaluate ecological quality of open-pit coal mines in four typical climatic-geomorphologic zones (arid Gobi, semi-arid grassland, semi-arid plateau, and karst plateau). Through comparative analysis of the evaluation results of four indices, combined with correlation analysis, spatial distribution identification, land cover response assessment, and validation with synchronous field measurement data from typical mining areas, we analyzed the adaptability and limitations of each index in open-pit coal mines across different climatic-geomorphologic zones. The results showed that the ecological quality assessment based on SurMEI exhibited the best performance (mean correlation coefficient of 0.810) in the four typical climatic-geomorphologic zones, demonstrating good adaptability in cross-regional evaluations. The performance disparities among the other three indices arose from mismatches between their index structures and regionally dominant ecological processes. RSEIs overestimated disturbances in humid areas due to excessive sensitivity to the normalized difference bare soil index. LSESCI exhibited misclassification in complex terrains, owing to instability of the brightness component derived from the tasseled cap transformation. RSEInew failed in arid zones because of the weak discriminative power of its added PM_2.5 indicator. Furthermore, spatiotemporal analysis based on SurMEI revealed significant differences in ecological restoration potential across different climatic-geomorphologic zones, with the highest potential in the karst plateau, intermediate in the semi-arid region (including grassland and plateau), and the lowest in the arid Gobi, indicating that ecological restoration should follow the principle of “zonal management”. This study would provide a theoretical basis for accurate monitoring of ecological quality and model optimization for open-pit coal mines across different climatic-geomorphologic zones.

Key words: remote sensing ecological quality assessment, climatic-geomorphologic zone, open-pit coal mine, index optimization, spatial and temporal variation