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Proceedings Paper

Estimation of sea surface spectrum using neural networks
Author(s): Jorge J. Miranda; Merce Vall-llossera; Adriano Camps; Ramon Villarino
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Paper Abstract

Sea surface salinity (SSS) measurement is one of the objectives of ESA’s SMOS (Soil Moisture and Ocean Salinity) Earth Explorer Opportunity mission. SMOS’s objective is to provide global soil moisture and sea salinity maps using the MIRAS L-band aperture synthesis interferometric radiometer. Since the sea salinity signature exhibits a very small brightness temperature dynamic margin, it can only be accurately retrieved if the sea surface emissivity at L-band is properly modeled. In addition to the sea salinity signature, other factors influencing the emissivity are the sea surface temperature, and the sea surface roughness induced by wind, the large scale roughness created by swell, and the foam emissivity. This article is focused on the estimation of the sea surface spectrum, which describes sea roughness, training a neural network with wind and roughness data obtained during WISE 2000/2001 (WInd and Salinity Experiment).

Paper Details

Date Published: 26 February 2004
PDF: 10 pages
Proc. SPIE 5233, Remote Sensing of the Ocean and Sea Ice 2003, (26 February 2004); doi: 10.1117/12.511214
Show Author Affiliations
Jorge J. Miranda, Univ. Politecnica de Catalunya (Spain)
Merce Vall-llossera, Univ. Politecnica de Catalunya (Spain)
Adriano Camps, Univ. Politecnica de Catalunya (Spain)
Ramon Villarino, Univ. Politecnica de Catalunya (Spain)


Published in SPIE Proceedings Vol. 5233:
Remote Sensing of the Ocean and Sea Ice 2003
Charles R. Bostater; Rosalia Santoleri, Editor(s)

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