## 3 Results
### Long-Term Characteristics of Three Products  
#### 3.2.1 Tendency and Correlation of LAI/FVC/GPP  
The left panels in Figure 7 present spatial distributions of vegetation change trends by employing the [PERSON]'s slope estimator. Note that the Mann-Kendall test not marked in the panel. All datasets generally display a large area of significant positive trends in the northeastern (e.g., Gonghe, Jianzha, Guide, Guinan counties, etc.) and northwest TRSR (e.g., Zhiduo and Golmud counties). A few pixels with negative trends among three products have been found in the northwestern and southern TRSR.  
Figure 6: Phenological difference (days) between (**a**,**b**) LAI and FVC, (**c**,**d**) FVC and GPP, and (**e**,**f**) GPP and LAI, varying with the ratio of vegetation pixel (left panels) and terrain niche index (right panels) in 2018 across TRSR.  
Table 3 shows the statistical results of the change trends of three products from the 2000 to 2018 growing season. A significant tendency is observed for 10.44% of the LAI pixels, including 5.63% positive trends and 4.81% negative trends, whereas the FVC analysis generates approximately 19.92% significant pixels (17.37% and 2.55% with positive or negative trends, respectively). In addition, the GPP produces about 5.47% significant pixels (5.31% positive and 0.16% negative).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Product**} & \multicolumn{2}{c}{**Trend**} & \multirow{2}{*}{**Paired**} & \multicolumn{2}{c}{**Correlation**} \\ \cline{2-2} \cline{5-8}  & \multirow{2}{*}{**Positive**} & \multirow{2}{*}{**Negative**} & \multirow{2}{*}{**Insignificant Changes**} & \multirow{2}{*}{**Products**} & \multirow{2}{*}{**Positive**} & \multirow{2}{*}{**Negative**} & \multirow{2}{*}{**Insignificant Correlation**} \\ \cline{2-2} \cline{5-8}  & & & & & & & \\ \hline LAI & 5.63\% & 4.81\% & 89.56\% & LAI\_FVC & 42.52\% & 0.09\% & 57.39\% \\ FVC & 17.37\% & 2.55\% & 80.07\% & FVC\_GPP & 34.70\% & 0.05\% & 65.25\% \\ GPP & 5.31\% & 0.16\% & 94.53\% & GPP\_LAI & 74.59\% & \textless{}0.01\% & 25.41\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistical results on the correlations and trends of LAI, FVC, and GPP products during 2000–2018 (\(\alpha\) = 0.05).  
Figure 7: Spatial patterns of the slope values estimated from Theil–Sen trend analysis of LAI (**a**), FVC (**c**), and GPP (**e**), and the r-values estimated from Spearman rank correlation coefficient analysis between LAI_FVC (**b**), FVC_GPP (**d**), and GPP_LAI (**f**) during 2000–2018 across the TRSR.  
The right panels in Figure 7 show the correlation between each of the two products using the Spearman rank correlation coefficient method from 2000 to 2018 growing seasons in the TRSR. The highly positive relationship pixels among all datasets have been found in the northeastern TRSR (e.g., Gonghe, Guide, Jianzha, Guinan, Xinghai counties, etc.), and northern or northwestern TRSR (e.g., Maduo, Qumalai counties, etc.). Conversely, there were a few negative pixels found in the Golmud, Nangqian, Yushu counties, etc. As far as the statistical result was concerned, the proportion of positive correlation pixels between GPP and LAI is 74.59%, while FVC-GPP and LAI-FVC is 34.70% and 42.52%, respectively (Table 3).