# Hybrid Methodology Using Sentinel-1/Sentinel-2 for Soil Moisture Estimation
## 5 Conclusions  
Different approaches have been proposed for SSM estimation from space. The goal is to improve estimates by combining change detection logic with empirical or other approaches based on an ANN. The study is based on Sentinel-1 and Sentinel-2 data tested on the ISMN moisture network.  
Relationships between temporal changes in radar signals and temporal changes in soil moisture are tested. Improved change detection relationships combine these effects with the contribution of vegetation through two optical and radar indices (_NDVI_ and VH/VV ratio). The integration of the effect of vegetation slightly improves the precision with an _RMSE_ that decreases slightly from 0.074 m\({}^{3}\)/m\({}^{3}\) to 0.073 m\({}^{3}\)/m\({}^{3}\) and 0.068 m\({}^{3}\)/m\({}^{3}\) for VH/VV and _NDVI_, respectively.  
Testing an ANN approach through numerous metrics based on radar and optical (VV, VH, VH/VV, _NDVI_, \(\Delta\)VV, incidence angle, etc.) time series illustrates precision within a 0.08 m\({}^{3}\)/m\({}^{3}\)-0.09 (m\({}^{3}\)/m\({}^{3}\)) range. These results are greatly improved with the integration  
Figure 7: Scatterplots of statistical parameters of the hybrid approach performance to retrieve SSM as a function of _NDVI_ values stations: (**a**) _RMSE_, (**b**) _Bias_.  
as input of soil moisture estimated from the change detection approach. Thus, we move on to precision below the bar of 0.07 m\({}^{3}\)/m\({}^{3}\) for the different possible combinations of metrics. Thus, it seems highly useful to propose this combination to improve the precision of the estimated soil moisture. Despite this improvement, there are some limitations at some stations, particularly related to the vegetation density and presence of forests or extreme climates with cold conditions. In the future, it would be very useful to propose a spatialization of this approach by considering auxiliary information of soil properties and land use for a better application of the proposed algorithms and improvement of proposed precision. In fact, this allows us to distinguish effects due more precisely to vegetation for which volume and attenuation scattering are different from one cover to another. For a high-resolution scale, this aspect, which is generally not considered for a low-resolution scale, seems important.  
[PERSON], [PERSON] and [PERSON] developed methods and analyzed the data; all authors contributed to the materials/analysis tools; and [PERSON] and [PERSON] wrote the paper. All authors have read and agreed to the published version of the manuscript. This study was funded by Projects; ESA No. 4000126684/19/I-NB \"ESA CCI+\" and TAPAS TOSCA/CNES. The data presented in this study are available in International Soil Moisture Network (ISMN) [[https://ismm.geo.tuwien.ac.at/en/](https://ismm.geo.tuwien.ac.at/en/)]([https://ismm.geo.tuwien.ac.at/en/](https://ismm.geo.tuwien.ac.at/en/)) and [[https://scihub.copernicus.eu/sites](https://scihub.copernicus.eu/sites)]([https://scihub.copernicus.eu/sites](https://scihub.copernicus.eu/sites)) (accessed on 16 May 2022). The authors thank the International Soil Moisture Network (ISMN) and the supporting networks for the availability of soil moisture data. The authors declare no conflict of interest.