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Semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces

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dc.contributor.authorOh, Y-
dc.contributor.authorSarabandi, K-
dc.contributor.authorUlaby, FT-
dc.date.accessioned2022-04-11T02:42:21Z-
dc.date.available2022-04-11T02:42:21Z-
dc.date.created2022-04-11-
dc.date.issued2002-06-
dc.identifier.issn0196-2892-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/26825-
dc.description.abstractA semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces is presented. Based on existing scattering models and data sets measured by polarimetric scatterometers and the JPL AirSAR, the parameters of the co-polarized phase-difference probability density function, namely the degree of correlation cc and the co-polarized phase-difference;, in addition to the backscattering coefficients sigma(vv)(0), sigma(hh)(0) and sigma(vh)(0), are modeled empirically in terms of the volumetric moisture content m(v) and the surface roughness parameters ks and kl, where k = 2pif/c, s is the rms height and l is the correlation length. Consequently, the ensemble-averaged differential Mueller matrix (or the differential Stokes scattering operator) is specified completely by sigma(vv)(0), sigma(hh)(0), sigma(vh)(0), alpha, and zeta.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectDISTRIBUTED TARGETS-
dc.subjectSCATTERING-
dc.subjectCALIBRATION-
dc.titleSemi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces-
dc.typeArticle-
dc.contributor.affiliatedAuthorOh, Y-
dc.identifier.doi10.1109/TGRS.2002.800232-
dc.identifier.wosid000177114500015-
dc.identifier.bibliographicCitationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, v.40, no.6, pp.1348 - 1355-
dc.relation.isPartOfIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING-
dc.citation.titleIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING-
dc.citation.volume40-
dc.citation.number6-
dc.citation.startPage1348-
dc.citation.endPage1355-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaGeochemistry & Geophysics-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryGeochemistry & Geophysics-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
dc.subject.keywordPlusDISTRIBUTED TARGETS-
dc.subject.keywordPlusSCATTERING-
dc.subject.keywordPlusCALIBRATION-
dc.subject.keywordAuthorbare soil surfaces-
dc.subject.keywordAuthordifferential Mueller matrix-
dc.subject.keywordAuthormicrowave backscattering-
dc.subject.keywordAuthorsemi-empirical model-
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