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Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4445 - 4460 Titre : Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data Type de document : Article/Communication Auteurs : Lian He, Auteur ; Rocco Panciera, Auteur Année de publication : 2016 Article en page(s) : pp 4445 - 4460 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] biomasse [Termes IGN] cultures [Termes IGN] décomposition d'image [Termes IGN] données polarimétriques [Termes IGN] filtre adaptatif [Termes IGN] humidité du sol [Termes IGN] image radar moirée [Termes IGN] polarimétrie radar Résumé : (Auteur) The aim of this paper was to estimate soil moisture in agricultural crop fields from fully polarimetric L-band synthetic aperture radar (SAR) data through the polarimetric decomposition of the SAR coherency matrix. A nonnegative-eigenvalue-decomposition scheme, together with an adaptive volume scattering model, is extended to an adaptive model-based decomposition (MBD) (Adaptive MBD) model for soil moisture retrieval. The Adaptive MBD can ensure nonnegative decomposed scattering components and allows two parameters (i.e., the mean orientation angle and a degree of randomness) to be determined to characterize the volume scattering. Its performance was tested using airborne SAR data and coincident ground measurements collected over agricultural fields in southeastern Australia and compared with previous MBD methods (i.e., the Freeman three-component decomposition using the extended Bragg model, the Yamaguchi three-component decomposition, and an iterative generalized hybrid decomposition). The results obtained with the newly proposed decomposition scheme agreed well with expectations based on observed plant structure and biomass levels. The new method was superior in tracking soil moisture dynamics with respect to previous decomposition methods in our study area, with root-mean-square error of soil moisture estimations being 0.10 and 0.14 m3/m3, respectively, for surface and double-bounce components. However, large variability in the achieved soil moisture accuracy was observed, depending on the presence of row structures in the underlying soil surface. Numéro de notice : A2016-884 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2542214 En ligne : https://doi.org/10.1109/TGRS.2016.2542214 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83048 [article]