Estimation of sea surface spectrum using neural networks

Jorge J. Miranda; Merce Vall-llossera; Adriano Camps; Ramon Villarino

doi:10.1117/12.511214

26 February 2004 Estimation of sea surface spectrum using neural networks

Jorge J. Miranda, Merce Vall-llossera, Adriano Camps, Ramon Villarino

Proceedings Volume 5233, Remote Sensing of the Ocean and Sea Ice 2003; (2004) https://doi.org/10.1117/12.511214
Event: Remote Sensing, 2003, Barcelona, Spain

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).

Citation Download Citation

Jorge J. Miranda, Merce Vall-llossera, Adriano Camps, and Ramon Villarino "Estimation of sea surface spectrum using neural networks", Proc. SPIE 5233, Remote Sensing of the Ocean and Sea Ice 2003, (26 February 2004); https://doi.org/10.1117/12.511214

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available