## 4 Results
### Spatial Variation of the EE from 2002-2022
#### 4.2.2 Global Spatial Variation of EE in the Study Area  
To ensure the accuracy of the scale information, a 1 km \(\times\) 1 km grid was used to resample the RSEI images, and 83,745 sample points were collected in each RSEI image. The global Moran index and local LISA clustering were used to perform spatial autocorrelation analysis. The global Moran index determines whether there is spatial autocorrelation in the EE, while the local LISA index can obtain the spatial autocorrelation of the local EE. Figure 13 shows the global Moran index of the EE. The global Moran index for 2002, 2007, 2012, 2017, and 2022 were 0.901, 0.923, 0.936, 0.937, and 0.966, respectively. These data indicate a very strong spatial correlation between the EE. Considering that the first and third quadrants contained the majority of the sample points, that is, H-H and L-L clustering, the study area indicates strong ecological aggregation characteristics. From 2002 to 2022, the Moran index showed a continuous upward trend, which was consistent with the changes in EE in the study area. Using local spatial autocorrelation, LISA clustering maps were created to show the exact distribution characteristics of the EE, as shown in Figure 14.  
The LISA cluster distribution map shows that H-H is mainly distributed in the loess hilly-guilly regions, and the vegetation cover in these areas has increased year by year due to the GGP policy. The distribution area of H-H increased rapidly between 2002 and 2012, until the vegetation entered the ecological succession stage in recent years, indicating that the GGP has improved the EE. On the other hand, L-L is mainly distributed in the river valley plain region, where urbanization is rapid and human production activities  
Figure 13: Global Moran index in the study area in (a) 2002, (b) 2007, (c) 2012, (d) 2017, and (e) 2022.  
are numerous, leading to continuous expansion of the L-L distribution area. Especially in the heavily populated urban areas, the L-L area gradually expanded from 2007 to 2022, indicating that rapid urbanization causes the deterioration of the EE. Furthermore, the chordal graph of RSEI transfer matrix is shown in Figure 15. Spatial transfer between different years is shown in the figure below, and the legend indicates the level of EE transfer (Figure 16). We also studied the transfer of EE since 2002. Figure 14: LISA clustering maps in the study area in (**a**) 2002, (**b**) 2007, (**c**) 2012, (**d**) 2017, and (**e**) 2022. Figure 15: Chordal graph of RSEI transfer matrix of (**a**) 2002–2007, (**b**) 2007–2012, (**c**) 2012–2017, and (**d**) 2017–2022. The figure indicates that in many ecological improvement regions, Excellent areas increased to 21,777.36 km\({}^{2}\) by 2022. Except for a few regions that do not change, the transfer pattern is generally a poor, fair, and moderate transfer to each other; then a moderate, good, and excellent transfer to each other. In the period 2002-2007, a total area of 6124.77 km\({}^{2}\) was transferred from the poor regions, of which 4847.52 km\({}^{2}\) were transferred to the fair regions and 1178.36 km\({}^{2}\) were transferred to the moderate regions. In the period 2007-2012, a total area of 3572.21 km\({}^{2}\) was transferred from the poor regions, of which 3172.84 km\({}^{2}\) were transferred to the fair regions and 397 km\({}^{2}\) were transferred to the moderate regions. In the period 2012-2017, a total area of 2106 km\({}^{2}\) was transferred from the poor regions, of which 2007.76 km\({}^{2}\) were transferred to the fair regions and 97.24 km\({}^{2}\) were transferred to the fair regions and 3485.81 km\({}^{2}\) was transferred from the poor regions, of which 3085.87 km\({}^{2}\) were transferred to the fair regions and 398.23 km\({}^{2}\) were transferred to the moderate regions. factors usually have a significant impact on the EE, with temperature and precipitation having a direct correlation with plant growth, and vegetation can promote EE improvement.