# First Vegetation Optical Depth Mapping from Sentinel-1 C-band SAR Data over Crop Fields
## 5 Discussion
### Complementarity of NDVI and VOD in Vegetation Monitoring  
At VV polarization, results show that VOD values obtained from the SAR data in ascending and descending mode fit the temporal dynamics of NDVI (R\({}^{2}\) varies from 0.39 to 0.61 for barley, fallow, oat, and wheat) (Figures 3 and 4). However, these VOD-VV values peak earlier than the NDVI by about 18 days (Figure 3). A possible explanation is that during the beginning of the senescence period (mainly in May for winter crop), the canopy begins to lose water content while photosynthetic activity  
Figure 14: Impact of 1 cm overestimation on VOD estimations: Bias (noisy VOD—reference VOD) and RMSE are plotted as a function of NDVI. Figure 13: Impact of 1 cm _Hrms_ overestimation on VOD estimations: Noisy VOD as a function of reference VOD. has not yet decreased; so that VOD, which is sensitive to the vegetation water content (VWC), begins to decrease while NDVI, which is sensitive to the vegetation photosynthetic activity, continues increasing or remains stable [31; 32]. Another possible explanation is that during the growing season the NDVI saturates earlier than VOD (namely, the peak in the vegetation photosynthetic activity cannot be well identified with the NDVI index) and thus the NDVI will decrease later than VOD. The value of 18 days, which represents the difference between NDVI peak date and VOD peak date, may be inaccurate since NDVI data are sometimes missing and the temporal resolution of computed VOD is 18 days. However, according to temporal profiles of NDVI and VOD in both growth cycles, this difference cannot be shorter than 18 days. On the other hand, [PERSON] et al. [33] showed that NDVI reached a peak earlier than VOD computed from ARMS-E. Similarly, [PERSON] et al. [10] showed that VOD computed from SMOS (L-band) peaked later than MODIS LAI values, with an estimated time difference of about 19 days. Such inconstancy may be related to the SAR technology and the used frequency. In this study, SAR C-band (5.4 GHz) data were used, whereas in the studies of [PERSON] et al. [33] and [PERSON] et al. [10] data used were provided from radiometers at 18.7 GHz and 1.4 GHz, respectively. Moreover, the use of the SAR data in both ascending and descending modes provides approximately the same VOD values, except for the periods from 13 May 2018 to 18 June 2018 and from 1 May 2019 to 1 June 2019 (Figure 3). During these periods, it is observed that VOD computed from ascending SAR images acquired at the end of the day (~18h00 UTC) is lower than VOD computed from descending SAR images acquired in the morning (~06h00 UTC). This observation may be explained by the fact that VWC is much lower at 18 h than at 6 h due to canopy water loss (stress and/or transpiration) which increases during the day, especially in the presence of high temperatures [7; 34]. Indeed, Figure 2 shows that between 3 May 2018 and 18 June 2018, the daily average temperature increased to a ~25 \({}^{\circ}\)C (daily maximum temperature varied between 24 \({}^{\circ}\)C and 33 \({}^{\circ}\)C). This may indicate that VOD-VV derived from S1 has the potential to monitor plants water status at the plot scale. This is consistent with results obtained at a large scale over the USA by [PERSON] et al. [35]. At VH polarization, VOD computed separately from S1 images in ascending and descending mode are weakly correlated to NDVI (R\({}^{2}\) varies between 0.1 and 0.5 for barley, fallow, oat, and wheat) (Figures 5 and 6). The VH signal results from the incident wave depolarization caused principally by volume scattering, namely multiple interactions between SAR microwave radiations and vegetation elements [36; 37]. Thus, VH observations are more sensitive to the vegetation structure than the vegetation water content [38; 39]. Moreover, multiple scattering mechanisms are not taken into account in the simple WCM model formulation. The used WCM describes soil surface scattering attenuated by vegetation canopy, an attenuation parameterized by the vegetation water content.