Title :
On the assessment of SMOS salinity retrieval by using Support Vector Regression (SVR)
Author :
Sabia, R. ; Marconcini, Mattia ; Katagis, T. ; Fernandez-Prieto, Diego ; Portabella, Marcos
Author_Institution :
ESA-ESRIN, Eur. Space Agency, Frascati, Italy
Abstract :
A sounding of the capabilities of a novel salinity retrieval strategy by means of Support Vector Regression (SVR) has been performed. SMOS brightness temperatures measurements and additional auxiliary parameters have been co-located with salinity data collected by ARGO buoys, which represented the ground-truth to be matched by the algorithm. Salinity fields estimated by the SVR are in good agreement with the ground-truth, suggesting that the chosen approach can be promising, despite its robustness and versatility are under further assessment over wider areas and time lags, and in various combinations of SMOS features.
Keywords :
regression analysis; remote sensing; salinity (geophysical); ARGO buoys; SMOS brightness temperatures measurements; SMOS features; SMOS salinity retrieval assessment; auxiliary parameters; ground-truth; salinity data; salinity fields; salinity retrieval strategy; support vector regression; Extraterrestrial measurements; Robustness; Sea measurements; Sea surface salinity; Support vector machines; Training; Ocean Salinity; Regression; SMOS; Support Vector Machines;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6723085