The Sentinel missions operational since 2015 for Sentinel 1 ((S1), radar C band, VV, VH polarizations) and 2016 for Sentinel 2 ((S2), optical and middle infrared range) provide data at high spatial and temporal resolution, well suitable for crop monitoring. Soil moisture products (SMP) developed from S1 and S2 using neural network techniques [1] are delivered at plot scale every 6 days via the Theia French public platform¹. Up to now, these products were computed and validated mainly on cereals and grasslands. Mediterranean plots are often small and present a wide variability of agricultural practices. Among them, orchards, which require high quantify of water for irrigation are not represented in SMP because of their structure heterogeneity. The objective of our study was twofold: -i) to test SMP products for various Mediterranean crops (including orchards) with different agricultural management for 3 years, -ii) to analyze the correlation between soil moisture measurements (sm) and spectral indices derived from S1 and S2 to monitor the water status of cherry trees. Various fields of the Ouvèze basin in Southeastern France were monitored with different ground measurements. Results revealed (i) that differences appear between SMP products and soil moisture due to variability within farming systems. Beyond a specific slope and vegetation threshold, the correlation does not improve significantly; (ii) In orchards plots, different models using spectral indices from S1 and S2 were evaluated to estimate sm and showed significant correlations with ground measurements: R2=0.72 with an RMSE < 0.05 cm³/cm³.