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Soil-moisture estimation from X-band data using Tikhonov regularization and neural netKseneman, Matej ; Gleich, DušanThis paper introduces soil-moisture parameter retrieval using high-resolution vertically polarized (VV) Spotlight TerraSAR-X data. The soil-moisture estimation of bare and vegetated areas is ... considered by using volumetric scattering, which is modeled with a bare-soil component and a component reflecting vegetation. The unknown coefficients of the soil-moisture model are estimated using the Tikhonov regularization scheme. A neural network is used in order to distinguish volumetric scattering from all the other types of scattering. The estimated volumetricsoil- moisture parameters are further enhanced by using a supervised feedforward backpropagation neural network. The proposed algorithm based on the Tikhonov regularization scheme, in combination with neural networks, provides good results for estimating volumetric-soil-moisture in an area covered with a small vegetation canopy.Source: IEEE transactions on geoscience and remote sensing. - ISSN 0196-2892 (Vol. 51, no. 7, Jul. 2013, str. 3885-3898)Type of material - article, component partPublish date - 2013Language - englishCOBISS.SI-ID - 16634134
source: IEEE transactions on geoscience and remote sensing. - ISSN 0196-2892 (Vol. 51, no. 7, Jul. 2013, str. 3885-3898)
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Database name | Field | Year |
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Kseneman, Matej | 29814 |
Gleich, Dušan | 20862 |
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