## 4 Discussion  
### Improvements to GPP Modeling with Vegetation Red-Edge Information  
Previous research confirmed that total canopy chlorophyll content and incident photosynthetic active radiation (PARin) are key drivers of GPP in many croplands [39; 45; 46]. Our results compared the relationships between VIs \(\times\) PARin and \(\mathrm{GPP_{EC}}\) in grasslands and EBF sites, where the VIs were derived with and without red-edge bands. The results of this study showed that red-edge-based VIs such as CIr and CIg coupled with PAR have a higher correlation with \(\mathrm{GPP_{EC}}\) than other VIs without red-edge information in GRA sites, which is similar to the results of previous research [48]. The red edge contains information on vegetation conditions and is sensitive to changes in chlorophyll; thus, red-edge-based VIs, such as CIr, can track the seasonal changes in the chlorophyll pigment pool [37; 52; 82]. The vegetation pigment pool plays an important role in long- or medium-term GPP estimations [36]; thus, red-edge VIs can significantly explain the temporal variance in GPP in cropland and grassland sites [39; 52; 83]. Furthermore, this study also tested the relationship between \(\mathrm{CIr}\times\mathrm{PAR_{in}}\) and \(\mathrm{GPP_{EC}}\) in the forest sites. However, \(\mathrm{GPP_{EVI}}\) was more representative of \(\mathrm{GPP_{EC}}\) than GPP derived from the red edge in the EBF sites, which was also shown in previous studies [48]. There was a small rRMSE difference between \(\mathrm{GPP_{CIr}}\) and \(\mathrm{GPP_{EVI}}\). This result indicated that \(\mathrm{GPP_{CIr}}\) could partly evaluate the variance in GPP in EBF sites. On the one hand, at WOM sites, as in EBF sites, the seasonal change in CIr was not significant (Figure 6). The total GPP was more limited by the incident PAR but not the CIr-related chlorophyll content; thus, under clear and cloudy conditions, the major limitation to GPP is only PAR. Research showed that the reflectance chlorophyll/carotenoid index is more sensitive to intra-annual changes in the pigment pool at evergreen sites [38]; thus, the red-edge-based VIs cannot track the seasonal changes in the pigment pool. Conversely, the light-use efficiency at evergreen forest sites is mostly controlled by water and PARin; thus, the seasonal changes in the chlorophyll content did not lead to significant stress and photosynthesis decline [84]. In addition, the \(\mathrm{VI}\times\mathrm{PAR_{in}}\)-based GPP model represented the  
Figure 11: Cross-site comparison of \(\mathrm{GPP_{EC}}\) and GPP modeling results, including MOD17A2H product (presented as \(\mathrm{Sietename_{MOD}}\)), \(\mathrm{GPP_{EVI}}\) (presented as \(\mathrm{Sietename_{EVI}}\)), and \(\mathrm{GPP_{CIr}}\) (presented as \(\mathrm{Sietename_{CIF}}\)). The \(\mathrm{GPP_{EVI}}\) and \(\mathrm{GPP_{CIr}}\) across selected EBF sites were estimated by \(1.93\times\mathrm{EVI}\times\mathrm{PAR}+2.45\) and \(0.32\times\mathrm{CIr}\times\mathrm{PAR}+2.56\), respectively. The \(\mathrm{GPP_{EVI}}\) and \(\mathrm{GPP_{CIr}}\) across selected grassland sites were estimated by \(1.33\times\mathrm{EVI}\times\mathrm{PAR}-0.5\) and \(0.31\times\mathrm{CIr}\times\mathrm{PAR}+0.05\), respectively. The units of \(\mathrm{GPP_{EC}}\), modeled GPP, and RMSE are \(\mathrm{gC}\)-m\({}^{-2}\)-day\({}^{-1}\). The black line in the middle is the 1:1 line. medium condition of monthly scale GPP that cannot fully catch the highest and lowest GPP values [23]. The accurate GPP value over a shorter time period should also consider the short-term changes in weather conditions. Thus, the LUE-based models considering short-term weather situations such as MODIS GPP exhibited better performance with \(\text{GPP}_{\text{EC}}\) than other \(\text{GPP}_{\text{VI}}\)[85; 86]. For cross-site studies in evergreen forests, a previous study also showed that the MODIS GPP exhibited better performance than the GPP estimated by the red-edge index [48].