Enhancing the spatial resolution of SMOS soil moisture data over Spain

A downscaling algorithm to improve the spatial resolution of SMOS soil moisture estimates using higher resolution visible/infrared (VIS/IR) data is presented. The algorithm re- lates VIS/IR parameters such as the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (T_s) to SMOS soil moisture estimates using the "universal triangle" concept, and gracefully combines the high accuracy of SMOS radiometric observations with the high spatial resolution of VIS/IR data into an optimal soil moisture product. In preparation for the SMOS launch, the algorithm was tested using acquisitions of the UPC Airborne RadlomEter at L-band (ARIEL) over the REMEDHUS soil moisture monitoring network in Zamora, Spain, and LANDSAT imagery. After SMOS launch, the algorithm was applied to a set of SMOS images acquired during the commissioning phase over the OZnet soil moisture monitoring site, in South-Eastern Australia, and MODIS NDVI/T_s data. Results from comparison with in situ soil moisture measurements showed that the soil moisture variability was effectively captured at 10 and 1 km spatial scales, without a significant degradation of the root mean square error. The potential application of this downscaling approach to generate high resolution soil moisture maps over the Iberian Peninsula in near-real time is now being as- sessed.