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Journals and Conferences
An inversion technique based on neural networks has been implemented to estimate surface roughness and soil moisture over bare fields using ERS and RADARSAT data. The neural networks were trained with a simulated data set generated from the Integral Equation Model. Later the networks were applied to a field data set spanning a wide range of surface… (More)
Based on Canadian Satellite (RADARSAT) synthetic aperture radar (SAR) images and simulations from a radar-backscattering model, we determined that conventional wet snow-mapping algorithms should perform optimally for a snowpack with a liquid-water content 3%, at low incidence angle ( = 20–30 ) and for a rather smooth surface (rms height ≤ 2.1 mm).
We study the capabilities of low frequency radar systems to sound the subsurface in arid countries. This approach is based on the coupling between two complementary radar techniques: the airborne Synthetic Aperture Radar (SAR) used in L-band (1.2 GHz) for imaging large scale subsurface structures, and the Ground-Penetrating Radar (GPR) used between 500 and… (More)