# First Vegetation Optical Depth Mapping from Sentinel-1 C-band SAR Data over Crop Fields
## 6 Conclusions  
In this study, an approach for Vegetation Optical Depth (VOD) mapping at plot scale has been proposed. This approach is based on retrievals from times series of Sentinel-1 (S1) images using the Water Cloud Model (WCM). The approach developed here is valid only for non-irrigated areas. The NDVI derived from Sentinel-2 images was used to evaluate the relevance of our VOD estimations. VOD values were computed separately at VV and VH polarizations and from ascending and descending modes.  
For VOD computed at VV polarization, results show that the temporal dynamic of the estimated VOD fits generally well with the temporal dynamics of NDVI. In general, a medium to good correlation between VOD and NDVI temporal dynamics was obtained (R\({}^{2}\) about 0.58, 0.39, 0.46, and 0.61 for barley, fallow, oat, and wheat, respectively). However, during the beginning of the senescence period (from 25/04/2018 to 15/05/2018 and from 20/04/2019 to 10/05/2019), VOD and NDVI values became uncorrelated. VOD started decreasing on 25/04/2018 in the first crop growth cycle and on 20/04/2019 in the second crop cycle due to a decrease in the canopy water content while NDVI continued increasing due to the increase in the vegetation photosynthetic activity. Moreover, results showed that in the presence of a high temperature over a well-developed canopy (NDVI reaching its peak value), VOD values computed from the SAR images acquired at -18h (Ascending mode) were lower than those computed from the SAR images acquired at -6h (Descending mode). This observation was attributed to changes in the canopy water status which leads to a decrease in VWC during the hot afternoon. Finally, our results showed that the temporal dynamics of VOD values computed from VH polarization do not perfectly match that of NDVI (R\({}^{2}\) lower than 0.4 for barley, fallow, oat, and wheat). It is likely due to the multiple-scattering mechanisms present in VH polarization and which is not considered in WCM formulation. In future, other more complex modelling approaches will be used to better account for these volume scattering effects.  
The developed approach should be applied to other agricultural areas with more crop types to better assess its relevance. Moreover, in a context of operational crop monitoring, future work will focus on improving the approach developed in this study to map VOD over irrigated agricultural areas. Finally, to well assess the relevance of VOD computation, estimated VOD values should be compared to in-situ measurements of VWC [43].  
Conceptualization, M.E.H. and N.B.; Methodology, M.E.H. and N.B.; Validation, J.-P.W., M.Z., C.A., J.-C.C., and I.F.; Formal Analysis, M.E.H. and N.B.; Investigation, M.E.H. and N.B.; Writing-Original Draft Preparation, M.E.H.; Writing-Review & Editing, N.B., J.-P.W., M.Z., C.A., J.-C.C., and I.F.; Supervision, N.B.  
This research was funded by the French Space Study Center (CNES, TOSCA program) and the National Research Institute of Science and Technology for Environment and Agriculture (IRSTEA).  
The authors wish to thank the French Space Study Center (CNES, TOSCA program) and the National Research Institute of Science and Technology for Environment and Agriculture (IRSTEA) for supporting this work. Moreover, the authors wish to thank the European Spatial Agency (ESA) for the distribution of Sentinel-1 and Sentinel-2 data, and the French land data center (Theia) for providing Sentinel-2 images corrected for atmospheric effects. Finally, authors wish to thank the General Direction of Rural Development of the Department of Agriculture, Livestock, Fishing and Food of the Generalitat of Catalunya for providing the SIGPAC data and in particular [PERSON].  
The authors declare no conflict of interest.