SAC-D/AQUARIUS SOIL MOISTURE PRODUCT DEVELOPMENT AND EVALUATION FOR PAMPAS PLAINS (ARGENTINA)

CINTIA BRUSCANTINI; FRANCISCO MATIAS GRINGS; FEDERICO CARBALLO; MATIAS BARBER; PABLO PERNA; HAYDEE KARZSENBAUM

Quebec

Simposio; IEEE International Symposium Geoscience and Remote Sensing (IGARSS); 2014

In this work, several retrieval algorithms were implementedto retrieve soil moisture (sm) and optical depth (τ ) fromAquarius/SAC-D observations. Currently used sm retrievalalgorithms (H- and V-pol Single Channel Algorithm, Mi-crowave Polarization Difference Algorithm) were computedover Pampas Plains, Argentina. The methodology of a novelBayesian algorithm developed was also presented, and itsresults were contrasted with the previous algorithms. Fur-thermore, an Artificial Neural Network (ANN) approach toretrieve sm from Aquarius brightness temperature was im-plemented and trained using SMOS Level-2 sm product.Finally, performance metrics for each algorithm were derivedusing SMOS L2 sm as benchmark product.