This study evaluates the accuracy of several recent remote sensing Surface Soil Moisture (SSM) products at sites in southwestern France. The products used are Soil Moisture Active Passive "SMAP" (level 3: 36 km x 36 km, level 3 enhanced: 9 km x 9 km, and Level 2 SMAP/Sentinel-1: 1 km x 1km), Advanced Scatterometer "ASCAT" (level 2 with three spatial resolution 25 km x 25 km, 12.5 km x 12.5 km, and 1 km x 1 km), Soil Moisture and Ocean Salinity "SMOS" (SMOS INRA-CESBIO "SMOS-IC", SMOS Near-Real-Time "SMOS-NRT", SMOS Centre Aval de Traitement des Données SMOS level 3 "SMOS-CATDS", 25 km x 25 km) and Sentinel-1(S1) (25 km x 25 km, 9 km x 9 km, and 1 km x 1 km). The accuracy of SSM products was computed using in situ measurements of SSM observed at a depth of 5 cm. In situ measurements were obtained from the SMOSMANIA ThetaProbe (Time Domaine reflectometry) network (7 stations between 1 January 2016 and 30 June 2017) and additional field campaigns (near Montpellier city in France, between 1 January 2017 and 31 May 2017) in southwestern France. For our study sites, results showed that (i) the accuracy of the Level 2 SMAP/Sentinel-1 was lower than that of SMAP-36 km and SMAP-9 km; (ii) the SMAP-36 km and SMAP-9 km products provide more precise SSM estimates than SMOS products (SMOS-IC, SMOS-NRT, and SMOS-CATDS), mainly due to higher sensitivity of SMOS to RFI (Radio Frequency Interference) noise; and (iii) the accuracy of SMAP-36 km and SMAP-9 km products was similar to that of ASCAT (ASCAT-25 km, ASCAT-12.5 km and ASCAT-1 km) and S1 (S1-25 km, S1-9 km, and S1-1 km) products. The accuracy of SMAP, Sentinel-1 and ASCAT SSM products calculated using the average of statistics obtained on each site is defined by a bias of about -3.2 vol. %, RMSD (Root Mean Square Difference) about 7.6 vol. %, ubRMSD (unbiased Root Mean Square Difference) about 5.6 vol. %, and R coefficient about 0.57. For SMOS products, the station average bias, RMSD, ubRMSD, and R coefficient were about -10.6 vol. %, 12.7 vol. %, 5.9 vol. %, and 0.49, respectively.