European Journal of Molecular & Clinical Medicine

The objective of this work was to find a model to estimate surface soil moisture
by using the available andfree satellite imagery data of synergy of single polarized C-band
sentinel-1 and Optical Sentinel-2 Data acquired in dry and wet seasons on study site in
Niger.Water cloud model (WCM) was selected in this study due to its ability to describe
backscattering coefficients interms of soil proprieties and vegetation proprieties. First, we
founded the relation between Sentinel-1 backscattering coefficients𝝈𝑽𝑽
𝟎 and 𝝈𝑽𝑯
𝟎 in Cbandthat
are adjusted to minimizevegetation effect, and ground measurement of soil
moisture [downloaded from the International Soil Moisture Network (ISMN)], using linear
regression with Gradient descent. The sensitivity of the SAR backscatter to in situ
measurement was estimated as 0.7 and 0.43db/Vol% for VV and VH polarizations,
respectively. Second, the Normalized Difference Vegetation Index (NDVI) was used as
vegetation descriptor in the WCM, it is extracted directly from the preprocessed sentinel-2
optical images. The Calibration of WCM consists in fitting the model against ground
measurements and estimated parameters for VV and VH polarization by minimizing the
sum of squares of the differences between the simulated and measured radar signal