## 4 Results
### Results of Sentinel-2 Satellite Data  
Based on [PERSON]'s theory [49], it was hypothesized that in vegetation canopy, fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bared soil (BS) can be resolved by using the linearly independent indices NDVI and CAI. Likewise, based on Sentinel-2A multispectral data, this study contributes to resolve mixed vegetation canopy pixels into fractions of illuminated vegetation, shaded vegetation and bare soil through indices NDCSI and BSI. NDCSI was proposed based on the UAV hyperspectral data. When applying for Sentinel-2 hyperspectral image, corresponding bands should be utilized. Band 4 and 8 of Sentinel-2A are calculated for the NDVI factor and band 5 (central wavelength at 705 nm, close to RE location of UAV data) are used as RE factor. [PERSON] [50] proposed a bare soil index (BSI) for more reliable estimation of the vegetation status where the vegetation covers less than half of the area. The basic logic of this approach is based on high reciprocity between bare soil state and vegetation state. \[BSI=\frac{\left[(B5+\text{B3})-(\text{B4}+\text{B1})\right]}{\left[(B5+\text{ B3})+(\text{B4}+\text{B1})\right]} \tag{4}\]  
where B1, B3, B4, B5 refer to Landsat TM Band 1, 3, 4 and 5. Sentinel-2A has the similar band settings with Band 2, 4, 8 and 11 correspondingly. In the scatterplot of NDCSI versus BSI, calculations of reflectance spectra from the whole Sentinel-2 image form a triangle; illuminated vegetation (IV) having a high NDCSI and intermediate values of BSI; shaded vegetation (SV) having both low NDCSI and low BSI values; bare soil (BS) having low NDCSI and high BSI (Figure 8). Based on the conceptual approach from Figure 8, the relative abundance of each fractional cover should be resolved by LSU if the location and spectra of pure endmembers is known. Endmember spectra can be obtained directly from satellite image, measured on the ground or extracted from the spectral library. In fact, spectra derived directly from images are generally better than those derived from the ground or in the spectral library because they more accurately account for any errors in sensor calibration and atmospheric correction [43]. Using Region of Interest (ROI) tool from ENVI software and scatterplot of NDCSI versus BSI, endmember spectra of illuminated vegetation (IV), shaded vegetation (SV) and bare soil (BS) can be obtained easily and accurately. Using LSU analysis (Equation (2)) and endmember spectra derived from the vertices of the triangle in scatterplot of NDCSI versus BSI, fractional cover results of illuminated vegetation (IV), shaded vegetation (SV) and bare soil (BS) from Sentinel-2A image (Figure 2) were obtained, shown as Figure 9.  
Figure 8: The conceptual approach for quantifying illuminated/shaded vegetation fractional cover using Sentinel-2A multispectral data, whose reflectance spectra form a triangle in the scatterplot of NDCSI versus BSI. Pure endmembers reflectance spectra of IV, SV and BS will be located in the vertices of the triangle. Reflectance spectra of mixed pixels of the three components will be located within the triangle. Forty typical vegetation sample pixels with different illumination/shadow proportions were selected and their fractional illuminated vegetation cover (FIVC) values were calculated. In addition, an accumulated sum reflectance of the visible spectrum (Band 2, 3 and 4 of Sentinel-2A) were acquired to represent the measured brightness information of the corresponding pixels. Correlations between the FIVC and the measured brightness values are shown in Figure 10.  
Based on Sentinel-2A multispectral data, the fitted linear relation between vegetation pixel's FIVC and measured brightness values reached a positive correlation of \(R^{2}=0.827\) (\(p<0.01\)). The results indicated that, combined with a nonlinear dependent vegetation index (for example, BSI in this study), the NDCSI owns an adequate capacity for quantitative expression of the fractional cover of illumination/shadow vegetation canopy.