*3.1. Ecological Environment Quality, Spatial and Temporal Evolution, and Driving Forces* 3.1.1. Evolution Trend Analysis

According to the statistical analysis of the average EEQ value from 2000 to 2020 (Figure 3), the overall EEQ of the study area showed an increasing trend. The mean value of RSEI increased from 0.5329 in 2000 to 0.6363 in 2020, i.e., an increase of 0.1034 or 19.40% in 20 years. The overall trend of EEQ in the research area is still improving steadily. The overall trend of RSEI from 2000 to 2011 was relatively stable, although there were some fluctuations. From 2011 to 2016, the RSEI began to improve, although, again, there were still some fluctuations. The overall trend showed a steady improvement. From 2016 to 2020, RSEI in the study area began to improve significantly and remained stable. According to the evolution trend, the turning point of RSEI in the study area was determined to be 2016. In combination with the human activity in the area, we focused on analyzing the spatial and temporal distribution of RSEI to achieve the research objectives of this paper. The Grain to Green Project began in 2000; the Karst Rocky Desertification Restoration Project was implemented in 2008; and the PAR was implemented in 2016. Considering the time interval of the study period and that the effect of ecological restoration projects is somewhat delayed, we focused on data of the spatial and temporal distribution of RSEI for the years 2000, 2005, 2010, 2015, and 2020.

#### 3.1.2. Spatial–Temporal Evolution Analysis of EEQ

For convenient comparison, the average RSEI value was divided into five grades according to the average value: poor (0–0.2), relatively poor (0.2–0.4), moderate (0.4–0.6), good (0.6–0.8), and excellent (0.8–1.0) [41]. The spatial distribution of RSEI values in the study area was characterized by higher EEQ grades in the southeastern part of Ceheng and Wangmo, and all regions were optimized after 2010 to some extent.

During 2000–2010, the EEQ values of the study areas were generally similar, i.e., excellent and good grades accounted for ~44% of the subject areas, particularly in the southeastern areas of Ceheng and Wangmo (Figure 4).

During the period 2010–2015, the proportion of EEQ attributable to poor and relatively poor grades decreased to 26.26%, which originated from areas mainly concentrated in north-central Xingren, south-central Pu'an, north-central Xinyi, and other regions. The proportion of excellent and good grades rose to 48.46%, which was attributable to the areas that were concentrated in the southeastern area of Ceheng and Wangmo. During this period, the EEQ grade remained the same in an area accounting for 42.48% of the total study area. The area that saw an EEQ reduction accounted for 24.80% of the study area. This area with reduced EEQ was mainly distributed in Wangmu, Ceheng, Pu'an, and Qinglong. In this period, the dominant EEQ grades were excellent and good (Figures 4 and A1, Table 1).


**Table 1.** The transition matrix of EEQ levels during 2010–2015.

During the period from 2015 to 2020, the proportion of areas with an EEQ grade of poor or relatively poor decreased to 17.64%, and the distribution was mainly concentrated in the key areas of urban development. The proportion of areas with excellent and good grades further increased to 63.35%, with the most concentrated contiguous areas in Ceheng, Wangmo, and southeast of Zhenfeng. The EEQ improvement regions were most concentrated in Qinglong and Pu'an, which were the areas with the most fragile ecological environment areas and the most prominent peasants–land conflicts. The area of reduced EEQ was mainly concentrated in the urban development areas, such as Xingyi, where the population was further concentrated, and socio-economic development was more important (Figures 4 and A1, Table 2).

**Table 2.** The transition matrix of EEQ levels during 2015–2020.


#### 3.1.3. RSEI Result Test

The Pearson correlation coefficient was used to test the RSEI results. The results are presented in Table 3, where the average correlation of RSEI and the four indicators reached a maximum of 0.953, 0.964, −0.739 and −0.945, respectively. The correlation between RSEI and NDVI, WET, NDISI was significant at the 0.01 level, indicating strong significance, and the correlation with LST was significant at the 0.1 level, indicating general significance.


