Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

COSMO SkyMed AO projects -soil moisture detection for vegetation fields based on a modified water-cloud model using COSMO-SkyMed SAR data

Full metadata record
DC Field Value Language
dc.contributor.authorKweon, S.-K.-
dc.contributor.authorHwang, J.-H.-
dc.contributor.authorOh, Y.-
dc.date.accessioned2021-12-02T04:45:23Z-
dc.date.available2021-12-02T04:45:23Z-
dc.date.created2021-11-30-
dc.date.issued2012-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/19098-
dc.description.abstractIn this study, we developed a soil moisture retrieval technique for vegetation fields using a modified water-cloud model. The water-cloud model has been a typical algorithm used to analyze scattering from vegetation fields for a long time, because it is simple to be used for retrieving a variety of information such as soil moisture and vegetation water mass. However, its accuracy has been questionable because the water-cloud model contains lots of approximations in the process of simplification. To improve the accuracy of the algorithm, we modified the water-cloud model with the estimation of parameters using a radiative transfer model. Soil moisture is retrieved from SAR images by the modified water-cloud model for vegetation fields and compared with in-situ measured ground truth data. © 2012 IEEE.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-
dc.titleCOSMO SkyMed AO projects -soil moisture detection for vegetation fields based on a modified water-cloud model using COSMO-SkyMed SAR data-
dc.typeArticle-
dc.contributor.affiliatedAuthorOh, Y.-
dc.identifier.doi10.1109/IGARSS.2012.6350825-
dc.identifier.scopusid2-s2.0-84873114488-
dc.identifier.wosid000313189401105-
dc.identifier.bibliographicCitationInternational Geoscience and Remote Sensing Symposium (IGARSS), pp.1204 - 1207-
dc.relation.isPartOfInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.citation.titleInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.citation.startPage1204-
dc.citation.endPage1207-
dc.type.rimsART-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaGeology-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryGeosciences, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.subject.keywordAuthorbackscattering coefficients-
dc.subject.keywordAuthorInversion algorithm-
dc.subject.keywordAuthorsoil moisture-
dc.subject.keywordAuthorvegetation canopy-
dc.subject.keywordAuthorwater-cloud model-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Electronic & Electrical Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE