The aim of this study is to estimate and map soil moisture (SM) from Cosmo-Skymed (X band) images acquired over an agricultural basin located in the center of the province of Buenos Aires, Argentina (Latitude: 37ºS; Longitude: 60ºW approximately). The adopted approach is empirical, with a correlation between backscattering coefficient (sigma_o) and soil moisture (SM) measures, obtained simultaneously with a satellite pass. Surface (0 to 10 cm) soil moisture was measured by means of the gravimetric method in 15 agricultural parcels (sites). The linear relation between radar signal backscattering (sigma_o) and field measured SM [SM(%) = b + a . sigma_o(dB)] shows diverse coefficients and adjustments (r²), depending on orbit direction and polarization (from r² = 0,28 for VV Ascending to r² = 0,69 for HH Descending). Using corresponding relation equations, images were translated from sigma_o into SM (%), obtaining the SM maps (for each polarization and orbit pass). Cross-validation between measured and calculated SM was performed, computing the Root Mean Square Error (RMSE) and Normalized Mean Square Error (NMSE). Better results were obtained from Descending images, with 6,3% < RMSE < 6,9% and 1,6 < NMSE < 2,0%). Results are compared with other experiences, and future expectations are outlined.