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 relates VIS/IR parameters such as the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (Ts) 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 RadIomEter 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/Ts 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 assessed.