## 5 Conclusions  
Utilizing the GEE platform in conjunction with Landsat TM/OLI remote sensing data, this study embarked on a comprehensive spatiotemporal dynamic monitoring and analysis of Jincheng City's ecological environmental quality over the past 32 years, thereby employing the RCEI as a metric. This study explored the spatial differentiation characteristics of the city's ecological environmental quality. The findings derived from the remote sensing assessment and the monitoring of spatiotemporal variations within the 1990-2022 timeframe revealed the following:  
1. The Resource Cities Ecological Index (RCEI) is a comprehensive evaluation index based on remote sensing information. It integrates the majority of the information from six ecological environmental indicators, the NDVI, EVI, WET, NDBSI, LST, and ICDI, through principal component analysis. This index enables an objective and quantitative assessment and monitoring of the spatial and temporal distributions and change characteristics of the ecological environmental quality in mining areas. 2. Based on an analysis spanning from 1990 to 2022, the RCEI of Jincheng City ranged between 0.6 and 0.8, indicating that the city maintained an overall ecological quality at the upper-middle level. During this period, the city's ecological environmental quality exhibited a general trend of improvement. 3. At the county-level scale, significant disparities in ecological quality were observed among various districts within Jincheng City. In particular, the central urban area and Gaoping County exhibited relatively lower ecological levels compared to other regions, with average RCEI values ranging from 0.4 to 0.5. This phenomenon was directly attributed to the dense distribution of coal mines and the high degree of urbanization in these areas. 4. The Moran's I values were all over 0.9, suggesting a positive spatial autocorrelation in the distribution of ecological quality within the study area. This implied that the spatial distribution of ecological quality exhibited a clustered pattern, deviating from a random distribution. Specifically, the high-high (H-H) clusters were primarily located in the high-altitude regions surrounding the study area, characterized by dense ecological vegetation and fewer mining areas. Conversely, the low-low (L-L) clusters were primarily situated in urban construction areas and regions with large-scale mining distributions, where human production and living activities were frequent. 5. This study revealed the close link between coal production and ecological quality by analyzing the buffer zones of the Sihe and Fenghuangshan mining areas. The high production in the Sihe Mine Area caused a significant decrease in the mean RCEI value within the core mining area (0-1 km), a phenomenon that highlights the profound impact of mining activities on the surrounding ecological environment. Meanwhile, the Fenghuangshan Mine Area ceased production and underwent ecological restoration in 2018, and by 2022, the mean RCEI value of the area significantly increased from 0.4-0.45 to 0.65. Although urban development led to a decline in the ecological quality of the area 5 km away, the ecological quality of the environment within the city still showed a trend of improvement year by year. This study provides a feasible method for evaluating the spatial and temporal changes in ecological environmental quality in resource cities. Selecting suitable remote sensing indicators, establishing a resource-based ecological environmental quality evaluation system, and carrying out the evaluation and monitoring of spatiotemporal changes hold great significance for ecological protection management and sustainable development in resource-based cities. Our assessment study entirely relied on Landsat images to construct the RCEI in the GEE platform, which provides a feasible method for evaluating spatial and temporal changes in ecological quality.