# GPP of a Chinese Savanna Ecosystem during Different
## 3 Results
### Comparison of the Conventional MODIS Products and GPP\({}_{\text{EC}}\)
#### 3.5.2 Comparison of the Simulated GPP Values during the Different Phenophases  
By using the GCC values, we could achieve fine phenophase division. We can further analyze the performance of the VPM and remote sensing data sources with different spatial resolutions during the different phenophases in the Yuanjiang savanna by comparing the HLS and MODIS VPM simulation results with the EC data at the corresponding phenological stages. Specifically, the HLS data for the Yuanjiang savanna in this study were collected from July 2015 onward. For VPM result comparison during the different phenophases, only data from 2015 that matched the date of the phenophase were used (namely, the DOY should match the 128 to 176 range, Table 4). Therefore, during the 2015 green-up phase, the amount of data was very small (Figure 11a). However, to ensure comparison completeness, these data were retained (Figure 11).  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Year** & **SOSOSOY (Green-Up)** & **POP\({}_{\text{DOY}}\)** & **EOS\({}_{\text{DOY}}\) (Green-Down)** \\ \hline
2015 & 128 & 176 & 296 \\
2016 & 105 & 186 & 265 \\
2017 & 102 & 169 & 268 \\
2018 & 91 & 158 & 220 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Division of phenological periods on the basis of the GCC value from near-surface remote sensing phenocam images, 2015-2018. The green-up stage represents the period (DOY) from the beginning of the spring growing season to the green peak, and the green-down stage represents the period (DOY) from the green peak to the end of the autumn growing season. SOSOSOY: Start of the season (day of the year). POP\({}_{\text{DOY}}\): Peak of production (day of the year). EOS\({}_{\text{DOY}}\): End of the season (day of the year).  
Figure 11: Linear regression equations with an intercept of 0 for the HLS VPM simulations compared with the EC data during the different phenophases from 2015 to 2018 (**a–d**) for the green-up phenophase of each year and (**e–h**) for the green-down phenophase of each year.  
After comparison, we found that the HLS VPM simulation results exhibited a better correlation and a lower simulation error for both the green-up (spring and summer seasons) phenophase (slope = 1.91, R\({}^{2}\) = 0.75) and the green-down (autumn and winter seasons) phenophase (slope = 1.39, R\({}^{2}\) = 0.78) (Figures 11 and S4). The RMSE values for the HLS VPM simulation were also lower, with green-up RMSEs ranging from 2.23 to 4.94 and green-down RMSEs ranging from 1.03 to 3.62 across the years (Table S1). The MODIS VPM simulation results also demonstrated favorable performance during both the green-up (slope = 2.61, R\({}^{2}\) = 0.75) and green-down (slope = 1.68, R\({}^{2}\) = 0.78) phenophases, but the simulation results in autumn and winter were better than those at the spring and summer phenological stages, respectively (Figures 12 and S4). The corresponding RMSE values for the MODIS VPM were greater than those for the HLS, with green-up RMSEs between 2.83 and 5.78, and green-down RMSEs between 2.89 and 4.74 (Table S1).  
In contrast, GPP\({}_{\text{MOD17A2}}\) did not effectively track the observed phenological changes. The GPP\({}_{\text{MOD17A2}}\) model simulations exhibited high instability during the green-up phase, with the 2015 and 2017 simulations indicating underestimation and the 2016 and 2018 simulations indicating overestimation. The RMSE values for the MOD17A2H green-up phase were significantly greater, ranging from 21.8 to 27.7, indicating greater variability and error (Table S1). Moreover, the R\({}^{2}\) values were low across the years, with the maximum occurring in 2016 (R\({}^{2}\) = 0.58) and the minimum occurring in 2017 (R\({}^{2}\) = 0.34). However, during the green-down phase, the model simulation values were overestimated, with a maximum overestimation of 62% in 2016 and a minimum overestimation of 2% in 2017. The RMSE values during the green-down phase for MOD17A2H were also consistently high, ranging from 22.7 to 25.4 (Table S1).