## 3 Results
### Analysis of Spatial Correlation between Snow Cover and NDVI  
#### 3.3.1 Spatial Differentiation of Snow Cover-NDVI Correlation Features  
In this study, only the correlation between the average annual NDVI values of vegetation during the growing season (April to October from 1981 to 2020) and the corresponding snow depth in the same period was calculated, excluding the influence of opposing phenological patterns between snow and vegetation on the spatial Pearson correlation test results. Our research limited its examination to relationships between snow cover and  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & & **SND** & \\ \hline NDVI & Mean & SD & R\({}^{2}\) \\  & 1.02 & 0.95 & 0.56 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Lag length (months) of the NDVI to SND (snow depth).  
Figure 7: Snow cover and NDVI year-by-year monthly average distribution.  
NDVI accounting for the appropriate temporal lag and emphasizes the eco-hydroological connection between the two variables.  
The results are shown in Figure 8. Over the whole plateau, the correlation between snow cover and NDVI was generally significant and negative. Significant positive correlations were found only in the northern QTP, Qaidam basin, Qinghai Lake basin, Hehuang valley, southern Tibet valley, \"Yi Jiang Liang He\" basin, and part of the southern part of the Hengduan Mountains, but the proportion of the plateau covered by these areas was generally small. Significant negative correlations were found in the western Himalayas and Kunlun Mountains, southern Qilian Mountains, Qinghai Plateau, Tanggula Mountains, and a large area in the northern part of the Transverse Ranges. The areas with positive correlations were relatively flat and low-elevation areas. By contrast, the areas with negative correlations were concentrated in the relatively high-elevation mountainous plateau areas.  
Thus, we analyzed the correlations between snow cover and NDVI in areas at different altitudes, and the results are shown in Table 3. The result showed that the correlation between snow cover and vegetation was related to changes in elevation. In particular, in the basin and valley areas with elevations \(<\)3000 m, most of the areas had negative snow cover-vegetation correlations, i.e., 54.45%, where most areas had insignificant positive correlations. Among the areas at 3000-4000 m, the proportion of the areas with significant negative correlations increased significantly. Among the areas at 4000-5000 m, the proportion of the areas with significant negative correlations increased, and they accounted for the majority, whereas the proportion of the areas with positive correlations decreased significantly. The areas with negative correlations accounted for nearly 77% of the alpine plateau areas at \(>\)5000 m, and the areas with significant negative correlations increased further, whereas the areas with significant positive correlations comprised the lowest proportion, with less than 5%. Thus, the negative correlation between vegetation and snow depth was more pronounced when the altitude was higher and vice versa.  
Figure 8: Geographical differences in snow depth–NDVI correlation.  
The opposite changes occurred in the snow cover and phenology of vegetation because the snow cover increased as the temperature decreased, which reduced the soil temperature and led to the death of vegetation, whereas increased temperatures decreased the snow cover and increased the soil temperature to melt the snow and replenish the soil moisture to allow the vegetation to grow and develop. As a consequence, the snow cover and vegetation were negatively correlated, and each was correlated with the altitude according to the differences in temperature. Thus, we found that vegetation was more significantly affected by the snow cover in high-altitude areas.