Soil moisture retrievals at L-band using a two-step inversion approach (COSMOS/NAFE'05 Experiment) - Archive ouverte HAL Access content directly
Journal Articles Remote Sensing of Environment Year : 2009

Soil moisture retrievals at L-band using a two-step inversion approach (COSMOS/NAFE'05 Experiment)

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Abstract

COSMOS (Campaign for validating the Operation of Soil Moisture and Ocean Salinity), and NAFE (National Airborne Field Experiment) were two airborne campaigns held in the Goulburn River catchment (Australia) at the end of 2005. These airborne measurements are being used as benchmark data sets for validating the SMOS (Soil Moisture and Ocean Salinity) ground segment processor over prairies and crops. This paper presents results of soil moisture inversions and brightness temperature simulations at different resolutions from dual-polarisation and multi-angular L-band (1.4 GHz) measurements obtained from two independent radiometers. The aim of the paper is to provide a method that could overcome the limitations of unknown surface roughness for soil moisture retrievals from L-band data. For that purpose, a two-step approach is proposed for areas with low to moderate vegetation. Firstly, a two-parameter inversion of surface roughness and optical depth is used to obtain a roughness correction dependent on land use only. This step is conducted over small areas with known soil moisture. Such roughness correction is then used in the second step, where soil moisture and optical depth are retrieved over larger areas including mixed pixels. This approach produces soil moisture retrievals with root mean square errors between 0.034 m3 m−3 and 0.054 m3 m−3 over crops, prairies, and mixtures of these two land uses at different resolutions.
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Dates and versions

ird-00389586 , version 2 (29-05-2009)
ird-00389586 , version 1 (25-06-2010)

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Khaldoun Saleh, Yann H. Kerr, Philippe Richaume, Maria-José Escorihuela, R. Panciera, et al.. Soil moisture retrievals at L-band using a two-step inversion approach (COSMOS/NAFE'05 Experiment). Remote Sensing of Environment, 2009, 113 (6), pp.1304-1312. ⟨10.1016/j.rse.2009.02.013⟩. ⟨ird-00389586v2⟩
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