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Article Dans Une Revue Remote Sensing of Environment Année : 2007

Estimates of surface soil moisture under grass covers using L-band radiometry

Résumé

The scope of this study is to establish the parameters of the L-band (1.4 GHz) Microwave Emission of the Biosphere model (L-MEB) for grass covers, and to assess surface soil moisture retrievals in areas covered by grass. L-MEB parameters are key ancillary information for the Soil Moisture and Ocean Salinity mission (SMOS) retrieval algorithm that produces estimates of the surface soil moisture from measurements of the surface brightness temperature at L-band. L-band data sets from three ground-based experiments over grass are analysed in this paper: BARC (orchard grass and alfalfa), ELBARA-ETH (clover grass), and SMOSREX (grass and litter from a field left fallow). Modelling of the brightness temperature using the zero-th order radiative transfer model in L-MEB indicates that the vegetation appears isotropic to microwaves propagating with horizontal polarisation, and that the single scattering albedo can be neglected. At vertical polarisation, non-zero scattering is observed for all the grass data sets. Surface soil moisture is retrieved with enough accuracy for all data sets as long as the soil and litter emission are calibrated beforehand. Then surface soil moisture and vegetation optical depth can be left as free parameters in the retrieval process. Finally, the study highlights the importance of detecting strong emission and attenuation by wet vegetation and litter due to rainfall interception in order to obtain accurate estimates of the surface soil moisture. The study illustrates how strong rainfall interception can be flagged straightforwardly using a microwave polarisation index.

Domaines

Hydrologie

Dates et versions

hal-00186320 , version 1 (08-11-2007)

Identifiants

Citer

Khaldoun Saleh, J.-P. Wigneron, Philippe Waldteufel, Patricia de Rosnay, M. Schwank, et al.. Estimates of surface soil moisture under grass covers using L-band radiometry. Remote Sensing of Environment, 2007, 109 (1), pp.42-53. ⟨10.1016/j.rse.2006.12.002⟩. ⟨hal-00186320⟩
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