# Crop Water Content of Winter Wheat Revealed with Sentinel-1 and Sentinel-2 Imagery
## 4 Discussion  
Correlation analysis between three enhanced radar polarization indices that are most sensitive to soil moisture and the water content of wheat ear, wheat stem and leaf, wheat crop, and soil in this study was showed in Table 6. Enhanced radar polarization indices are less sensitive to crop canopy water content than soil water content. Because removed the influence of vegetation water content through the use of the water cloud model did not significantly affect the radar backscattering coefficient, and it showed that the backscattering coefficient directly extracted by Sentinel-1 radar  
Figure 6: Map of winter wheat crop water content in Gaocheng District on 25 May 2017 based on Sentinel-1 SAR data (**a**) and on 28 May 2017 based on Sentinel-2 data (**b**). images in vegetation-covered areas, such as farmland, can directly retrieve soil moisture and that vegetation had little effect on soil moisture inversion [44]. The enhanced Sentinel-1 radar polarization indices correlated better with soil water content than did the original radar polarization indices. This suggests that the enhanced radar polarization indices constructed from dual-polarized Sentinel-1 radar image in our study can retrieve accurate estimates of soil moisture, even in regions covered by crops. Through compared two polarization parameters, VH and VV, of the Sentinel-1 radar images and found that the inversion of vegetation water content based on VV was more accurate than that based on VH. Previous study found that VV was more sensitive to soil moisture [19]. It shows that the VV of dual-polarized radar data is more sensitive to vegetation water content and soil water content than VH when using water cloud model. The result of wheat crop water content inversion based on Sentinel-1 showed that modeling sample points and verification sample points all showed substantially consistent model accuracy in our study. Compared with the previous study that simulated C-band polarization data, and then invert the vegetation canopy water content based on semi-empirical model constructed by cross-polarization ratio, incidence angle, and frequency [25], our study has relatively higher inversion accuracy. This shows that the C-band enhanced radar polarization index combined with water cloud model has a well accuracy in the inversion of vegetation water content. Previous study has also found that the L-band RVI was highly correlated with wheat canopy water content [45]. The inversion result of wheat canopy water content based on C-band radar is similar to that of the above study, which indicates that the proposed method in our study can effectively estimate crop wheat canopy water content in farmland areas. In addition, previous studies used the brightness temperature of passive microwave to invert vegetation water content, compared with our study, the higher accuracy of vegetation water content inversion can be obtained from these [46; 47]. However, Sentinel-1, as an active microwave sensor, has higher spatial resolution compared with passive radar. It indicates that Sentinel-1 can be used to invert vegetation water content at field scale. In previous study, based on the Compact-polarimetric (CP) SAR data simulated by Radarsat-2 full-polarization SAR data, the rice canopy water content was inverted using CP backscattering coefficients and the water cloud model, which obtained a very high inversion accuracy [48]. Compared with the inversion results of CP SAR, the inversion accuracy of Sentinel-1 data for crop canopy water content in our study is lower. It is because that the polarization index of Sentinel-1 data confined to dual-polarization is generally less correlated with soil moisture content than full-polarization SAR data in agricultural areas [49; 50]. In our study, determination of the expression of model parameters was based on the principle of least fitting coefficients and did not attempt linear regression or nonlinear regression expression between sensitive SAR polarization indices and soil water content.