• 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