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Radiometric Performance of SMOS Full Polarimetric Imaging.

Authors :
Wu, Lin
Torres, Francesc
Corbella, Ignasi
Duffo, Nuria
Duran, Israel
Vall-llossera, Merce
Camps, Adiano
Delwart, Steven
Martin-Neira, Manuel
Source :
IEEE Geoscience & Remote Sensing Letters; Nov2013, Vol. 10 Issue 6, p1454-1458, 5p
Publication Year :
2013

Abstract

This work has been conducted in the framework of several projects devoted to assess the performance of the Soil Moisture and Ocean Salinity (SMOS) mission full-pol measurement mode. Since its launch in November 2009, SMOS is producing dual-polarization brightness temperature synthesized images that are yielding a high scientific return. However, these images are affected by a non-negligible spatial amplitude error, the so-called spatial bias (SB), that degrades geophysical parameter retrieval. This effect is particularly detrimental in SMOS polarimetric images where spatial bias is masking the polarimetric physical signature to a large extend. This paper presents a method to mitigate SMOS spatial bias by taking into account the co- and cross-polar antenna patterns in the image reconstruction algorithm through the, so called, full-pol G-matrix (FPG). The method is validated by producing spatial bias maps out of the comparison between SMOS full-pol images and an accurate polarimetric brightness temperature model of the ocean. This model has been provided to SMOS ESLs (Expert Support Laboratories) by LOCEAN (Laboratoire d'Océanographie et du Climat, France) as a test bench to validate and improve SMOS Level 1 (L1) data. Finally, a radiometric performance summary table comparing spatial bias and radiometric sensitivity between this new FPG approach and SMOS current co-polar G-matrix approach (CPG) is provided. This paper presents the best quality SMOS polarimetric images, which may lead a breakthrough in the science returns of the mission. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
1545598X
Volume :
10
Issue :
6
Database :
Complementary Index
Journal :
IEEE Geoscience & Remote Sensing Letters
Publication Type :
Academic Journal
Accession number :
91256463
Full Text :
https://doi.org/10.1109/LGRS.2013.2260128