## 4 Discussion
### Outlook for High-Spatial-Resolution Satellite GPP Mapping  
Our results demonstrated that the high-spatial-resolution and multi-temporal Sentinel-2 red-edge data corresponded well with GPPEC. The red-edge-based vegetation index Clr coupled with PAR showed less bias with GPPEC than the other VIs at all sites. We successfully mapped the spatio-temporally continuous GPP near the footprint region at each site based on the local relationship of red-edge VIs and GPPEC. Cloud cover affected the correlation between GPP and VIs (Figure 5). We selected Clr as an example to evaluate the relationship between GPP and VI. With the VI rebuilt on a daily scale, the correlation between GPP and VI \(\times\) PAR is similar under clear sky and cloudy days. Although the rRMSE of the daily GPP estimation at WOM was low, the rRMSE of Clr was lower on clear sky days than on cloudy days. The YNC site showed similar results, with an rRMSE reduced by 0.04 on clear days compared with the overall rRMSE. However, the key coefficients of a and b in the relationship of Clr-PARin-GPP had 20-50% difference under gap-filled Clr-based GPP and non-gap-filled values. On the one hand, cloud cover change affects the amount of PARin, which leads to bias in GPP estimates. Shaded leaves and sunlit leaves received different amounts of PARin under different sky conditions, and they had different LUEs in the same tree; thus, the relationship of VI-PARin-GPP differed under clear sky and cloudy conditions [90]. Therefore, the tower-based spectra measurement under different levels of PARin could help determine the calibration coefficients a and b for the relationship between VI and GPP [91; 92; 93; 94]. However, because the optical remote-sensing method cannot obtain effective images under cloudy conditions, the representativeness of the rebuilt VI time series depends on the effective VI that appears in the standard interval. There are two possible ways to improve the performance of GPPVI for capturing the seasonal and shorter temporal trend. One on hand, in order to get more effective satellite-based data during the cloudy conditions, one can apply multi-source remote-sensing data to improve the VI quality for rebuilding the time series VI during the peak of growing season [95]. The amounts of high-spatial-resolution remote-sensing data are increasing, such as Landsat-8 Operational Land Imager (OLI) and Chinese GF Wide-Field Camera (WMV), whereby the combination of these sensors can both improve the spatial resolution and revisit period [96]. This increase in data benefits the GPP mapping ability on a regional and continental scale. One the other hand, the chlorophyll-related VIs (such as Clr and EVI) are more related to the seasonal change of GPP, but not the short-term change [52]. Therefore, further research can apply some red-edge-related VIs for detect the seasonal change of chlorophyll content and couple the weather condition stress and chlorophyll fluorescence to capture short-term GPP variance [97; 98]. For regional- or continental-scale mapping, a series of stable values for coefficients a and b is important. Similar coefficients of a and b in the Clr-PARin-GPP relationship were shown at the YNC and RIG sites. Thus, a cross-site comparison with one set of coefficients for GPPCIr showed high correlation and low uncertainties with GPPEC at the two grassland sites (Figure 11b). This result suggested that GPPCIr could be used to map GPP at a large scale. However, the modeled GPP showed significant systematic bias compared with GPPEC because, at each forest type, the relationship between GPPVI and GPPEC was not a constant value across these sites. These data showed that high uncertainties occurred if one set of coefficients was used to estimate GPP with GPPCIr across the EBF sites (Figure 11a). There were several reasons for this result. The canopy chlorophyll content changes slowly at the EBF sites [99]. Unlike EVI, which changes slowly during the growing season, Clr is highly affected by the canopy chlorophyll content and the amount of available data.