This work presents the calibration and evaluation of an optical-passive microwave method for retrieving soil moisture (SM) at regional scale using remote sensing and reanalysis data. Several data sets were used, such as the bipolarized brightness temperature provided by SM and Ocean Salinity (SMOS) L3 brightness temperature product, the Normalized Difference Vegetation Index (NDVI) from moderate resolution imaging spectroradiometer (MODIS), the soil temperature and water content of the first 0-7 cm of depth from the ERA-Interim reanalysis, and 13 land cover classes obtained from the ECOCLIMAP database. The method was applied over Chile between 28°S and 43°S for 2010-2012. The data set was used to calibrate and evaluate a semiempirical approach for estimating SM, first by using only the data from SMOS and ERA-Interim and then also including the MODIS vegetation indicator. Results were analyzed for every land cover class using the determination coefficient (r2), the coefficients obtained from the regressions, and the unbiased rootmean-square difference (ubRMSD). Results showed an increase in the average r2 for all classes when a vegetation index was used in the calibration of the approach. The increases in r2 ranged from 3% for the crop class, to 49% for the closed shrubland class. The ubRMSD presented a decrease in its value of up to 1% m3/m3 for the woodlands, open shrublands, and woody shrublands classes and up to 2% m3/m3 for the closed shrubland class. These results contribute to the use of single linear and semiempirical regressions to estimate SM at regional scale based on SMOS L-band bipolarized brightness temperature.Read less <