## 3 Results
### Spatial Distribution of GPPCIr  
We used 30-m resampled Sentinel-2 data to quantify the spatial distribution of non-red-edge VIs and red-edge VIs (Figure 7). The coefficient of variance (CV) values of the red-edge CI in the EBF sites in January 2018 were 0.56, 0.16, and 0.14 for CUM, TUM, and WOM, respectively. The CVs of the EVIs near each site were 0.40, 0.12, and 0.08 for CUM, TUM, and WOM, respectively. In the forest sites, the CV of the red-edge-based CIr exhibited a higher spatial difference than the non-red-edge-based EVIs. The spatial variance in CIr was higher in the natural forest of TUM than at WOM. The CIr showed 11 value levels; however, the EVI showed concentrated values between \(-2\) standard deviations (STDs) and 2 STDs, whereas the artificial forests, such as those at the WOM site, were more homogeneous than the natural forests and still showed eight major levels of CIr values compared with the five levels in the EVI. The spatial heterogeneity at the CUM site showed large differences in CIr around the center of the image, but it showed a similar range of EVI around the site. Figure 5: The relationship between daily GPPCIr and GPPCPC under different percentages of cloud cover. The dates with daily clear sky index (CSI) \(>\) 0.8 (blue circles) are defined as clear days, whereas CSI \(<\) 0.8 (red squares) indicates cloudy days. Figure 6: Seasonal change in GPPC, incident photosynthetic active radiation (PARin), and red-edge chlorophyll index (CIr) during the research period (PAR in MJ-day\({}^{-1}\), GPP in gC-m\({}^{-2}\)-day\({}^{-1}\)). We mapped the range of GPP at five \(3\times 3\)-km sites based on their Clr \(\times\) PAR-GPP relationship, as shown in Tables 3 and 4. The GPP exhibited higher seasonal variance at the GRA sites than at the EBF sites. Figure 8 shows the annual GPP variance at these sites. The central footprint of CUM was forest, while the other parts were grassland, croplands, and artificial land cover (Figure 1). The forest component showed low intra-annual variance (CV \(<\) 0.2) throughout the year, whereas the grass component showed high intra-annual GPP variance (CV \(>\) 0.4). The other two forest sites were mostly covered by the EBF, showing CV ranges of 0.2 to 0.4 and 0 to 0.4 for WOM and TUM, respectively. For the grassland sites, the RIG site showed an annual GPP with a CV range from 0.3 to 0.8, and the YNC showed a CV range from 0.4 to 0.8. The land-cover reference image from Google Earth was used for comparison, as shown in Figure 1, which showed that the annual GPP variance in grassland and croplands was much higher than that in the EBFs. Figure 7: Hierarchical normalized vegetation index of Clr and enhanced vegetation index (EVI) near flux towers. All of the VI values in the \(3\times 3\)-km spatial window were normalized from 0 to 1 and then classified by the different levels of standard deviation. The subfigures show the Clr and EVI values from 1 January to 10 January 2018, under conditions of no cloud cover. The spatial resolution is 30 m.  
Figure 8: Spatial differences in GPP in the footprint region of each site. We set the footprint as a 3 \(\times\) 3-km region. The GPP was mapped by using the rebuilt CIr over a 16-day interval coupled with the PAR coefficient at each site, as shown in Tables 3 and 4. The GPP variance is the CV of the GPP in each pixel (standard deviation (STD)/mean value) throughout the research period. The pixels in gray are the regions without rebuilt VIs or non-vegetation components. The spatial variance in GPP differed among the different seasons. Figure 9a shows the GPP differences on different dates. The GPP showed high variance at the forest sites (TUM, WOM). During the peak of the growing season (December to January), each site showed higher GPP variance than that in the winter (July). Unlike the standard deviation, which was high at the peak of the growing season, the GPP showed less spatial variance at the TUM and WOM forest sites than at the other sites, with CV values less than 0.15 in all seasons (Figure 9b).