## 4 Discussion
### Importance of Reflectance and NDVI  
Recent studies have used reflectance or NDVI to present most of the vegetation information used in predicting SIF (K  
reflectance and NDVI were mainly used to provide canopy structure-related information, which was mainly represented by the fraction of PAR absorbed by green leaves in Equation (2).  
The canopy structure influences the re-absorption, scattering and escape probability of emitted SIF photons [25; 50; 79], and the reflectance and NDVI can provide structural information [33; 80]. The NDVI was designed to enhance the vegetation information contained in the canopy reflectance. However, the NDVI characteristic may not be well learned by the random forest machine-learning model using red/near-infrared reflectance, although the relationship between the NDVI and the two reflectances is completely deterministic [81; 82]. Therefore, the NDVI and red/near-infrared reflectance were both included in the random forest model in this study, although this may seem some redundant.  
[PERSON] and [PERSON] [28] and [PERSON] et al. [21] used seven MODIS reflectance bands to present SIF information. It was found that the first four bands (red, near-infrared, blue and green) can provide most of the vegetation information [39; 83]. In our case, we found that the improvement in R\({}^{2}\) achieved by using seven bands rather than four was less than 0.1, which is consistent with the results found by [PERSON] et al. [22]. Therefore, only four MODIS reflectance bands were subsequently used in this study.  
Near-infrared and red bands are most commonly used to represent the vegetation structural and pigment concentration information. The near-infrared band contains structural information, which influences the SIF escape probability (and also the NDVI) [50; 84]. The near-infrared reflectance has a linear relationship with the canopy scattering scale, and has an inverse relationship with the leaf albedo and the amount of light intercepted by the canopy (the complement to the fraction of light that reaches the soil and does not interact with the canopy) [25; 26; 49] chlorophyll concentration has less impact on the escape ratio and reflectance in the near-infrared SIF [85]. The red reflectance is strongly associated with pigments apart from the xanthophyll carotenoids, and can provide information about the absorption [83; 86]. Red radiation is strongly absorbed by chlorophyll, and the absorption increases with chlorophyll concentration [26; 87].  
The blue and green bands also contain helpful information for predicting SIF. Firstly, reflectance is mainly used to provide information related to fPAR. PAR covers the spectral window from 400-700 nm, which includes the blue, green and red bands. This means that the red band alone cannot well represent fPAR-related information. Secondly, as carotenoids transfer energy to chlorophyll molecules during photosynthesis [76], the use of the blue and green bands can help in the measurement of carotenoid concentration and variation, which are related to the amount of absorption. The blue reflectance is strong related to chlorophyll and carotenoid (including carotenes and xanthophylls) absorption; and green reflectance is sensitive to the difference between two extreme situations of xanthophyll carotenoids with higher absorption [83; 86]. Thirdly, the green reflectance slowly changes with the pigment pool size at the seasonal scale [63]. Additionally, the Photochemical Reflectance Index (PRI), which is calculated form the green reflectance, is related to canopy photosynthetic efficiency over different kinds of species and time scales [88; 89]. Many researchers have shown that the PRI can represent NPQ [83; 90; 91].  
Therefore, BRDF-corrected reflectance (at the red, near infra-red, blue and green bands) and the NDVI are all important in predictions of SIF, and also provide a certain amount of structural information.