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Communication Dans Un Congrès Année : 2010

L-band emission of rough soil surface covered with a grass litter layer including a moisture gradient: comparison between experimental data and a numerical model approach

Résumé

In the context of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, we present a study of the emission of rough surfaces at 1.4 GHz and the effects on this emission of a grass litter layer covering the surface. A new approach for the calculation of rough surface scattering and emission at L-band is used. This approach relies on the use of ANSYS's numerical computation software HFSS (High Frequency Structure Simulator), which in turn solves Maxwell's equations using the Finite Element Method (FEM). The interest of this approach is that it can be extended to calculate the emission of complicated multilayer media, including features such as volume effects and inclusions, as well as rough surfaces. This is therefore especially useful for the problem of the emission from soil-litter systems in forests. We are currently working to use FEM method to compute also thermal effects and water infiltration effects in ground. Coupling electromagnetic and thermal computation we will be able to study scattering of media such as permafrost or effects of rapid changes in temperature condition. It can be very useful for global observations with a frequent repeat coverage. In the present study we will present water infiltration in ground effects on the emissivity of soil-litter system. In particular we will focus on those effects on the previous results.
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Dates et versions

hal-00512478 , version 1 (30-08-2010)

Identifiants

  • HAL Id : hal-00512478 , version 1
  • PRODINRA : 247362

Citer

François Demontoux, Heather Lawrence, Valery Mironov, Kosolapova L.G., Arnaud Mialon, et al.. L-band emission of rough soil surface covered with a grass litter layer including a moisture gradient: comparison between experimental data and a numerical model approach. The 3rd International Symposium on Recent Advances in Quantitative Remote Sensing: RAQRS'III, Universitat de València (UV). ESP., Sep 2010, Valencia, Spain. pp.12. ⟨hal-00512478⟩
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