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• Multi-source data are integrated to effectively construct RSEI in successive years. • The characteristics of ecological quality variation have been revealed. • The weak positive trend delayed by mining has been proved. • The extent and area of the better or worse trend have been identified. Coal-based industries are critical to the contemporary world's growth, while the environmental degradation associated with the industry is also increasing. In this study, we develop the Remote Sensing Ecological Index (RSEI) and map its distribution from 2000 to 2020 using the Muli coalfield near Qinghai Lake as the research object. This index is obtained by fitting four components that are critically related to the quality of the ecological environment, including greenness, humidity, heat and dryness, to finally obtain a desirable evaluation. The results illustrate that: (1) The RSEI displayed an overall increasing trend on the time scale, but it also went through three lengthier phases of trend changes. In space view, the RSEI of the unaltered areas has greatly improved, while the damaged areas are clearly concentrated in the study area's northwestern region, where mining is common. (2) In the trend test, the overall variation of RSEI was found to be around 3%. RSEI significantly increased in 69.57% of the study region, whereas RSEI decreased dramatically in 30.43% of the study area. (3) In opencast mining disturbed areas and undisturbed areas, a different quality structure can be discovered, with Moderate and Good levels predominating in disturbed areas and Good and Excellent levels predominating in undisturbed areas. The ecological decline in damaged areas significantly hampered the overall upward trend of RSEI. (4) The Globalmoran's I value was 0.558, 0.546, 0.409, 0.574, and 0.680 in 2000, 2005, 2010, 2015, and 2020, respectively, showing a positive association between regional distribution of ecological environment quality and that opencast mining does really degrade that quality. It has been demonstrated that our evaluation accurately classify the local environment as affected by opencast mining, making it crucial for studying the relationship between coal mining and ecological quality. This index can also be utilized in the future when conducting surveys of other regions of intense human disturbance. [ABSTRACT FROM AUTHOR]