## 3 Results and Analysis
### Comparison of Reflectance among Different Sensors  
A correlation analysis was used to compare the accuracy of the reflectance among the three different sensors at different LAI values. The reflectance values of ZY-3 MUX, GF-1 WFV, and HJ-1 CCD in the red and NIR bands were extracted, according to the coordinates of the LAI field measurements. The relationships between the LAI field measurements and the corresponding reflectance in the red and NIR bands are shown in Figure 9. The reflectance values of ZY-3 MUX, GF-1 WFV, and HJ-1 CCD decreased with increasing LAI, and the reflectance values were much more scattered in the red band than in the NIR band (Figure 9a). The R\({}^{2}\) values between the reflectance and the LAI were \(0.49,0.50,\) and \(0.59\) for ZY-3 MUX, GF-1 WFV, and HJ-1 CCD, respectively. However, the reflectance of the red band for HJ-1 CCD easily reached saturation when the LAI was greater than 3. The reflectance in the NIR band increased with LAI (Figure 9b) in all sensors, and the R\({}^{2}\) values between the reflectance and the LAI were higher than in the red band, which were 0.66, 0.45, and 0.56 for ZY-3 MUX, GF-1 WFV, and HJ-1 CCD, respectively. The degree of variation of the NIR reflectance was higher than the variation in the red reflectance. This was especially true for ZY-3 MUX, which had the highest reflectance values. However, the trends of the NIR reflectance variations were more coincident among ZY-3 MUX, GF-1 WFV, and HJ-1 CCD. Figure 8: LAI inversions up-scaled to 16 m spatial resolution from ZY-3 MUX plotted against GF-1 WFV LAI inversions (**a**) and LAI inversions up-scaled to 30 m spatial resolution from ZY-3 MUX (**b**) or GF-1 WFV (**c**) plotted against HJ-1 CCD LAI inversions for pure (blue dots) and mixed (red dots) pixels. To determine the influences of different sensor spectral response functions, the reflectance in the red and NIR bands for Landsat-8 OLI and the three Chinese satellite sensors (i.e., ZY-3 MUX, GF-1 WFV, and HJ-1 CCD) were simulated from the PROSAIL model based on the same values of input variables presented in Table 4, with SZA at 30\({}^{\circ}\), VZA at 0\({}^{\circ}\), and LAI varying from 0 to 8 at intervals of 0.1. The theoretical differences in reflectance in the red or NIR band were compared between the simulations of Landsat-8 OLI and those of ZY-3 MUX, GF-1 WFV, or HJ-1 CCD (Figure 10). The results showed that the individual reflectances of ZY-3 MUX, GF-1 WFV, and HJ-1 CCD were higher than those of Landsat-8 OLI in the red band (Figure 10b) and lower than those of Landsat-8 OLI in the NIR band (Figure 10c). The reflectance in the red band for HJ-1 CCD and that in the NIR band for GF-1 WFV were each close to the corresponding bands of Landsat-8 OLI. The differences in reflectance in the NIR band were larger than those in the red band. These differences occurred because the NIR spectral response function of Landsat-8 OLI was much narrower than those of the Chinese satellite sensors for ZY-3 MUX, GF-1 WFV, and HJ-1 CCD, as shown in Figure 2. In addition, the difference in reflectance between Landsat-8 OLI and each of the Chinese satellite sensors was greatly influenced by the sensor's spatial resolution. The reflectance that was theoretically closest to that of Landsat-8 OLI was that of HJ-1 CCD with 30 m spatial resolution, followed by that of GF-1 WFV. To analyze the stability of the different sensors, the actual differences of reflectance in the red and NIR bands were compared between Landsat-8 OLI and each of ZY-3 MUX, GF-1 WFV, and HJ-1 CCD. The differences in reflectance in the red band are larger than those of Landsat-8 OLI and the NIR  
CCD. The reflectance data of the four sensors were compared at the same spatial resolution of 30 m\({}_{3}\) thus, the mean values of reflectance for ZY-3 MUX and GF-1 WFV were compared with Landsat-8 OLI reflectance values. Approximately 7000 pixels of uniform cropland were extracted from Landsat-8 OLI, ZY-3 MUX, GF-1 WFV, and HJ-1 CCD images.