## 3 Results
### Model-Based NDVI Future Trend Prediction
To more distinctly reveal the characteristics of NDVI changes in China under four SSP scenarios, this study conducted a spatial distribution analysis of NDVI change from 2023 to 2100 under different SSP scenarios, as shown in Figure 6. The results indicate that the spatial patterns of NDVI change exhibit certain differences across scenarios. Generally, under lower greenhouse gas emission scenarios (e.g., SSP126), negative change areas are more widely distributed, especially in Inner Mongolia, the northeast, and parts of southern China. In contrast, higher emission scenarios (e.g., SSP370 and SSP585) show an increased proportion of positive change areas, particularly in some inland regions and Tibet. Specifically, under the SSP126 scenario, with aggressive mitigation measures and sustainable development strategies leading to strict control of greenhouse gas emissions, over half of the regions (61.20%) experienced NDVI decline. Under SSP245, slightly more than half of the regions (55.82%) showed a downward trend in NDVI. For SSP370, a marginally greater extent of regions (55.21%) also exhibited declining NDVI trends. However, under SSP585, the proportion of regions with NDVI increase exceeded those with a decrease, with 44.01% of regions experiencing NDVI reduction and 55.99% showing growth. Moreover, the magnitude of NDVI change varies among scenarios; the maximum increase under SSP370 far surpasses other scenarios, reaching 0.7362, indicating significant vegetation growth in some areas, possibly due to adaptation measures or natural ecosystem recovery. Under SSP585, both the maximum increase and decrease exhibit larger magnitudes (maximum increase: 0.7366, maximum decrease: \(-\)0.3158). Spatially, the distribution of negative and positive change areas differs by scenario. Under SSP126, NDVI decreases predominantly occur in central and eastern Inner Mongolia, northeastern China, the Sichuan Basin, Yungui  
Figure 5: Spatial distribution of predicted NDVI values in China under four SSP scenarios: panels (**a**–**d**) correspond to the NDVI of China in 2100 under the SSP126, SSP245, SSP370, and SSP585 scenarios, respectively. Plateau, and southeastern hills, while positive change areas are relatively limited, concentrating in southern Shanxi and Shandong. Under SSP245, although the distribution pattern of negative change areas resembles SSP126, its extent narrows, mainly restricted to the northeast, Yungui Plateau, and Sichuan Basin regions, while positive change areas extend to small high-value zones in southeastern Tibet. Under SSP370, NDVI declines concentrate in the northeast, Yungui Plateau, and Sichuan Basin, whereas positive change areas appear in Hunan and Jiangxi, with small high-value zones also emerging in southeastern Tibet. Under SSP585, negative change areas are minimal, confined to Yunnan, eastern Inner Mongolia, and South China, while positive change areas form a strip-like distribution along the central border of Inner Mongolia and include small high-value zones in southeastern Tibet. The concentration of negative change areas may correlate with these regions' higher sensitivity to climate change and impacts of temperature and precipitation changes, while the increase in positive change areas could be associated with enhanced ecological adaptability or climatic conditions becoming more favorable for vegetation growth in these regions.