## 4 Discussion
### Analysis of the Correlation between Component Indicators and RCEI  
To ensure the integrity of information and the precision of quantitative assessments within the specified scale, this study integrated the intrinsic attributes of the study area with its classification patterns and ecosystem characteristics. Consequently, image data were resampled to a spatial resolution of 1 km \(\times\) 1 km. A total of 3043 sample points were extracted from RCEI imagery spanning from 1990 to 2022 to ascertain the spatial correlation of variables and their magnitudes. Moreover, this research examined the interplay between positive vegetation indices (NDVI, EVI), hydric and xeric indicators (WET, NDBSI), and adverse indicators (surface LST and coal dust index ICDI) in relation to the RCEI through three-dimensional spatial projections, as depicted in Figure 12.  
Figure 11: Positions of different RCEI sample loci in an OLI image, as well as in an RCEI image and OLI image (RGB) for different RCEI levels. (**a**) Location of samples with different RCEI levels in the RCEI image, (**b**) Location of samples with different RCEI levels in OLI images, (**c**) Images of national parks with excellent RCEI levels, (**d**) OLI images of the Sihe mine with poor RCEI levels, (**e**) OLI images of the YiCheng mine with poor RCEI levels, (**f**) OLI images of the Gu mine located in urban areas with poor RCEI levels, (**g**) Images of national parks with good RCEI levels located on the urban fringe, (**h**) OLI images of national wetlands with excellent RCEI levels.  
Figure 12a revealed a direct correlation between the NDVI, EVI, and RCEI, where higher index values corresponded to elevated RCEI scores, indicating the effectiveness of these vegetation indices in reflecting ecological environmental quality. Conversely, Figure 12b demonstrates the contrasting impacts of the hydric indicator WET and the xeric indicator NDBSI on the RCEI, with increased RCEI values aligning with higher WET and lower NDBSI values, thus indicating a positive association with ecological quality for the WET and a negative one for the NDBSI. Figure 12c illustrates the inverse relationship of the LST and ICDI with the RCEI, where higher values of these indicators were associated with reduced ecological quality.  
As shown in Figure 13, the RCEI index showed a significant correlation with several ecological indicators, indicating its effectiveness in synthesizing these indicators. As revealed in Figure 13, the RCEI showed positive correlation with the NDVI, EVI, and WET indicators and negative correlation with the NDBSI, ICDI, and LST indicators. By comparing the six-year average correlation coefficients, we found that the NDBSI had the highest correlation coefficient among the six single indicators, which reached 0.7. However, the six-year average correlation coefficient of the RCEI was 0.765, which exceeded that of the NDBSI by 0.065. The average correlation coefficients of the RCEI were higher than those of any single ecological environmental indicator during the period from 1990 to 2022, which further confirmed the importance of the RCEI in assessing the ecological quality of resource-based cities.  
Figure 12: 3D scatterplot of the WET, NDVI, EVI, NDBSI, LST, ICDI and RCEI at sampling points: (**a**) 3D spatial relationship between the RCEI, NDVI, and EVI; (**b**) 3D spatial relations between the RCEI, NDBSI, and WET; (**c**) 3D spatial relations between the RCEI, ICDI, and LST.