# Vegetation Health in China Is Severely Compromised by Drought, Wet and Heat Stress Events
## 3 Results
### PSR Models Most Accurately Reflect Vegetation Health
#### 3.1.2 Evaluation of the Vegetation Health Assessment System Construction Effectiveness  
The LAI is a crucial ecological indicator for measuring vegetation health, effectively assessing the physiological state and overall health of vegetation [40]. Compared to the Normalized Difference Vegetation Index (NDVI), LAI represents half of the total leaf area per unit ground area, which is a fundamental property of vegetation and a critical climatic variable. It provides a more accurate depiction of canopy structural dynamics and vegetation responses to stress [41]. This study evaluates the construction effectiveness of the vegetation health assessment system by analyzing the fitting results and correlation between the VHI and the LAI over each decade. The results indicate that the CIM assessment system shows low correlation and explanatory power for the years 2001 (\(R^{2}\) = 0.22, \(r\) = 0.35), 2010 (\(R^{2}\) = 0.22, \(r\) = 0.35), and 2020 (\(R^{2}\) = 0.23, \(r\) = 0.36) (Figure 4A), suggesting a weak linear relationship with LAI. This implies that the CIM's ability to evaluate vegetation health during these periods is limited. In contrast, the TOPSIS assessment system shows progressively increasing correlation and explanatory power over each decade, rising from \(R^{2}\) = 0.36, \(r\) = 0.51 in 2001 to \(R^{2}\) = 0.52, \(r\) = 0.65 in 2020. This trend indicates that the TOPSIS method increasingly aligns with LAI measurements over time, as its comprehensive calculation method more thoroughly considers multiple factors related to vegetation health (Figure 4A(d-f)). Additionally, the PSR model consistently demonstrates strong correlation and explanatory power across all three years, with a particularly high \(R^{2}\) = 0.66 in 2001, indicating a stable positive relationship with LAI (Figure 4A(g-i)). Figure 3: **(A)** Spatial distribution of CIM-constructed vegetation health systems. **(B)** Spatial distribution of TOPSIS-constructed vegetation health systems. **(C)** Spatial distribution of PSR-constructed vegetation health systems. Five-year VHI changes constructed using CIM, TOPSIS, and PSR models. **(a–e)** show the spatiotemporal patterns of VHI for the years 2000, 2005, 2010, 2015, and 2020, respectively. **(f)** illustrates the spatial pattern of the average VHI from 2000 to 2020. Figure 4: _Cont._  
NPP, as a key indicator of an ecosystem's carbon capture capacity, reflects the efficiency of vegetation in fixing carbon from the atmosphere through photosynthesis. Generally, high NPP indicates healthy and actively growing vegetation. Healthy vegetation can effectively absorb more carbon dioxide, enhancing carbon sequestration and thereby contributing to combating climate change [42]. Compared to GPP, NPP places greater emphasis on net carbon gain, making it more suitable for evaluating long-term vegetation growth trends and the impacts of environmental stress. The results indicate that for the CIM system, the correlation and explanatory power with NPP gradually increase over the years, with \(R^{2}\) = 0.20, \(r\) = 0.31 in 2001, \(R^{2}\) = 0.24, \(r\) = 0.38 in 2010, and \(R^{2}\) = 0.32, \(r\) = 0.47 in 2020 (Figure 4B(a-c)), showing a slow but steady strengthening of the relationship between CIM and NPP over time. The TOPSIS method demonstrates a significant upward trend during the same period with correlation and explanatory power increasing from \(R^{2}\) = 0.29, \(r\) = 0.43 in 2001 to \(R^{2}\) = 0.57, \(r\) = 0.69 in 2020 (Figure 4B(d-f)). This notable improvement indicates that the TOPSIS method has become more effective in explaining the relationship between NPP and vegetation health, reflecting an increased fitness over time. The PSR model also shows stable growth during the evaluation period with the correlation increasing from \(R^{2}\) = 0.51 in 2001 to \(R^{2}\) = 0.53 in 2010 (Figure 4B(g-i)). Although there was a slight decline in 2020, the overall performance remains stable. SIF is a critical indicator for assessing vegetation photosynthetic efficiency.