DocumentCode :
2188817
Title :
Preliminary results of SMOS salinity retrieval by using Support Vector Regression (SVR)
Author :
Sabia, R. ; Marconcini, M. ; Katagis, T. ; Fernández-Prieto, D. ; Martinez, J. ; Portabella, M.
Author_Institution :
ESRIN, Eur. Space Agency, Frascati, Italy
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
2629
Lastpage :
2632
Abstract :
A prospective sounding of the capabilities of a novel salinity retrieval by means of Support Vector Regression has been performed. Co-located SMOS measurements and additional auxiliary parameters have been considered, whilst salinity data collected by ARGO buoys 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 needs to be assessed over wider areas and time lags, and in various combinations of SMOS features.
Keywords :
oceanographic techniques; regression analysis; support vector machines; ARGO buoys; SMOS features; SMOS salinity retrieval; auxiliary parameters; colocated SMOS measurements; salinity fields; support vector regression; whilst salinity data; Extraterrestrial measurements; Robustness; Sea measurements; Support vector machines; Training; Ocean Salinity; Regression; SMOS; Support Vector Machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6350389
Filename :
6350389
Link To Document :
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