## 3 Results  
### Historical Trend Analysis of NDVI  
To investigate the long-term dynamic changes in NDVI across China, spatial changes were analyzed, as shown in Figure 1. The results indicate that, overall, most regions in China maintained relatively stable NDVI values from 2001 to 2023. However, specific areas exhibited distinct change patterns. Notably, significant increases in NDVI were observed in southeastern Henan Province and northwestern Anhui Province, likely attributable to successful deforestation projects, optimized farmland management, and ecological restoration initiatives. These activities typically enhance vegetation growth and land productivity, leading to increased NDVI values. Conversely, a slight decline in NDVI was noted in the northwestern part of Inner Mongolia Autonomous Region and its border with Gansu Province, possibly due to intensified drought, overgrazing, or agricultural reclamation exerting pressure on natural vegetation. A significant decrease in NDVI occurred in a small area northeast of Heihe City in Heilongjiang Province, which may be associated with localized environmental degradation, water scarcity, or other anthropogenic disturbances. It is worth noting that despite their limited extent, southern Xiaogan City and Qianjiang City in Hubei Province showed substantial NDVI increases, reflecting the positive impact of effective local ecological conservation measures or urban greening projects. The slight reduction in NDVI surrounding these increased zones might be induced by edge effects from urban expansion or agricultural activities [91]. Furthermore, an in-depth analysis using STL decomposition was conducted on the monthly NDVI data from 2001 to 2023 for this region, with results presented in Figure 2. The analysis revealed a significant annual cyclic variation pattern in the NDVI values, specifically showing that the NDVI values reach their lowest point in winter (particularly  
Figure 1: Spatial distribution of significant NDVI change trends in China from 2001 to 2023: significant decrease (slope \(\leq-0.003/\text{year},\,|\,Z|>1.96\)), slight decrease (\(-0.003/\text{year}<\text{slope}\leq-0.00005/\text{year},\,|\,Z|>1.96\)), stable (\(-0.00005/\text{year}<\text{slope}<0.00005/\text{year},\,|\,Z|>1.96\)), significant increase (\(0.003/\text{year}\leq\text{slope},\,|\,Z|>1.96\)), slight increase (\(0.00005/\text{year}\leq\text{slope}<0.003/\text{year},\,|\,Z|>1.96\)). in January and February), while peaking in summer (July and August). Although there are some fluctuations in the NDVI values each year, the amplitude of seasonal changes remains largely consistent, indicating that the NDVI variations strictly follow a distinct seasonal pattern. Post 2015, positive peaks (indicative of peak vegetation growth) began to exhibit a gradually ascending trend, with the magnitude of both positive and negative peaks appearing to increase year by year. In recent years, there has been a gradual improvement in spring and autumn vegetation cover, evidenced by an increasing amplitude of seasonal fluctuations. The trend component, representing the overall change in NDVI over time after removing seasonal and random factors, shows an upward trend from 2001 to 2023. Although interspersed with fluctuations, this growth trend became particularly significant since 2010, reflecting an increase in vegetation cover in China during this period. This phenomenon may be associated with a series of ecological restoration policies implemented by the Chinese government, such as the \"Three-North Shelter Forest\" project and the \"Grain for Green\" policy, aimed at enhancing forest coverage and improving environmental quality [92; 93]. The residual component, denoting the variation in data unexplained by seasonal and trend factors, typically exhibits small values. Notably, the residual reached its minimum value of \(-0.0263\) in June 2001; conversely, the maximum positive value of \(0.0174\) was observed in June 2002.