## 4 Discussion  
### Potential of OCO-2 SIF and MODIS VIs in Estimating the Autumn Crop Production of China  
The main goals of this study are (1) to explore the relationship between the OCO-2 SIF data and the government's autumn crop production statistics and establish a simplified model for estimating autumn crop production while using OCO-2 SIF; (2) to compare the differences between the SIF/57\", SIF/71', EVI', NDVI' for estimating the autumn crop production; and, (3) to analyze the factors affecting the estimation accuracy. Therefore, it is a new attempt to use satellite remote SIF data for crop production estimation. Crops yield can be estimated while using remotely sensed GPP [47]. Additionally, GPP based on GOME-2 SIF has been used to predict the crop yield in previous study [46]. Thus, GPP and crop yield (production) are related. On the other hand, SIF is mainly determined by Absorbed photosynthetically active radiation (APAR) [30; 48], which is the key to link SIF and GPP [45]. Therefore, we conclude that OCO-2 SIF data are closely related to autumn crop production. Besides, the spatial resolution of MODIS VIs is finer than OCO-2 SIF and the OCO-2 SIF product is discrete, which indicates that VIs is more advantageous than SIF. However, the autumn crop production that is predicted by SIF' is more accurate than VIs', with higher R\({}^{2}\), lower RMSE, and MAE. It proved that SIF' is more effective than VIs'. In addition, the R\({}^{2}\) of SIF'-crop production statistics were 0.548-0.716 for SIF/71' and they were 0.526-0.692 for SIF/57\" (Table 1). The mean R\({}^{2}\) of SIF'-crop production statistics were 0.662 and 0.643 for SIF/71' and SIF/57\", respectively (Table 1). SIF/71' was more related to the autumn crop production than SIF/57\". However, SIF/57\" performed better than SIF/71' when estimating autumn crop production, which indicated that SIF/57 is more sensitive to photosynthesis than SIF/71 in this study region. The result is consistent with another study, which showed that SIF/57 has a stronger correlation with tower GPP than SIF/71 [24]. This phenomenon could be explained by 771 nm falling farther away from the peak emission on the SIF spectrum, which indicated that SIF/57 has higher retrieval precision than SIF/71 [28; 30]. The crop production statistics were highly correlated with EVI/NDVI data during the leaf constant period. In this study, the autumn crop production statistics were more strongly correlated with SIF data during July than the other period, which is the leaf constant period. This finding can be explained  
Figure 4: The spatial distribution of the government’s autumn crop production statistics, the percentage of deviation of the autumn crop production estimated by using SIF/57 in 2016, and the percentage of cropland covered by solar-induced chlorophyll fluorescence (SIF) data in each province (**a**); and, topography of Chinese cropland (**b**). by the strong photosynthesis during the constant leaf period. In addition, according to previous studies, July represents the peak growing season for autumn crop [31], which explains why the most relevant correlation between SIF and production is July. SIF757' performed best when estimating the autumn crop production in China (R\({}^{2}\) = 0.678, \(p<0.01\); RMSE = 748.901 ten kilotons; MAE = 567.629 ten kilotons). The performance of SIF757' is better than the estimation performance of satellite Earth Observation (EO) time-series products for wheat, barley, and grain maize productions in Europe (approximately R\({}^{2}\) = 0.583) [49]. Moreover, this performance is close to the crop phenology and a combination of EVI2 (the MODIS two-band Enhanced Vegetation Index) and NDVI estimating maize, soybean productions in America (approximately R\({}^{2}\) = 0.69-0.70) [16]. In addition, the correlations between VIs' (EVI' and NDVI) and autumn crop production were not much different among the months, whereas the correlations between SIF' (SIF757' and SIF771') and autumn crop production were much different among months.