## 4 Discussion
### Biophysical Performance of Vegetation Indices for the Sugarcane Plantations
Several global GPP datasets derived from satellite-based LUE models are also available to the community, including the Terra/MODIS Gross and Net Primary Production (GPP/NPP) data product (MOD17A2) [56; 83] and the GPP dataset from VPM simulations (GPP\({}_{\text{VPM-Globe}}\)) [55]. We compared the seasonal dynamic of the GPP\({}_{\text{EC}}\), GPP\({}_{\text{VPM-Site}}\), GPP\({}_{\text{VPM-NCEP}}\), GPP\({}_{\text{MOD17A2}}\), and GPP\({}_{\text{VPM-Globe}}\) at the two sites (Figure 10). The GPP\({}_{\text{MOD17A2}}\) was much lower than the GPP\({}_{\text{EC}}\), GPP\({}_{\text{VPM-Site}}\), and GPP\({}_{\text{VPM-Globe}}\) during the plant growing season at the two sites (Figure 10a,b). The scatterplots of GPP\({}_{\text{MOD17A2}}\), GPP\({}_{\text{VPM-Site}}\), GPP\({}_{\text{VPM-NCEP}}\), and GPP\({}_{\text{VPM-Globe}}\) versus the GPP\({}_{\text{EC}}\) over the plant growing seasons at the two sites showed strong linear correlations between the GPP\({}_{\text{EC}}\) and other GPP estimates (Figure 10c,d). Using the GPP\({}_{\text{EC}}\) as reference, the GPP\({}_{\text{MOD17A2}}\) underestimated the GPP by 61% at the USA site and 59% at the Brazil site. The GPP\({}_{\text{VPM-Globe}}\) underestimated the GPP by 35% at the USA site and 40% at the Brazil site. The large underestimation by the global data products (GPP\({}_{\text{MOD17A2}}\) and GPP\({}_{\text{VPM-Globe}}\)) at the two sites can be attributed to the maximum LUE parameter used in the global simulations. For the MOD17A2 GPP/NPP product, the C3 maximum LUE parameter was used in its model simulation, as the land cover map using (MCD12C1 C55) does not separate the C3 and C4 crops. For the GPP\({}_{\text{VPM-Globe}}\) product [55], the VPM simulations used a mix of C3 and C4 maximum LUE parameters for croplands and the land cover maps (MCD12C1, C55). The maximum LUE parameter values of the C4 plants are substantially higher than those of the C3 plants [84]. The results from this study clearly highlight the urgent need for developing annual maps of C3 and C4 crops so that model simulations can use the appropriate C3 or C4 maximum LUE parameter (\(\varepsilon 0\)) for specific crop function types. Such comparison analyses also suggest that the global GPP data products to estimate the sugarcane GPP at local and regional scales should be used cautiously. Sources of Errors and Uncertainty in Predicted GPP\({}_{\text{VPM-site}}\) at Sugarcane EC Flux Tower Sites  
VPM simulations at the two sugarcane sites have several sources of error or uncertainty, including in situ climate datasets, time series MODIS vegetation indices, model parameters, and land cover types within the MODIS image pixels and the footprint of EC flux tower sites. The maximum LUE parameter values are estimated by various estimation methods and directly affect GPP simulations at the ecosystem level [85; 86]. Several previous in situ studies have reported that the LUE varied under rain-fed and irrigated conditions--for example, for sugarcane varieties in Sri Lanka, the LUE parameter ranged between 1.63 and 2.09 g dry biomass MJ\({}^{-1}\) under irrigated and between 0.71 and 1.03 g dry biomass MJ\({}^{-1}\) under rain-fed conditions [87]. Another publication reported that the maximum LUE for sugarcane at tropical region in Australia ranges from 1.7 g dry biomass MJ\({}^{-1}\)[88] to 2.0 g dry biomass MJ\({}^{-1}\)[89]. One field experiment in Brazil showed that maximum LUE parameter ranged between 1.74 and 2.28 g C MJ\({}^{-1}\) (0.85-1.12 g C mol\({}^{-1}\) PPFD) [90]. In the above-mentioned papers, the LUE was calculated using the linear regression between the cumulative radiation intercepted and the aboveground dry weight. In addition, many studies analyzed the PAR and gross primary production data to estimate the maximum LUE parameter (LUE\({}_{\text{GPP}}\)) [21].