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Microwave vegetation index from multi-angular observations and its application in vegetation properties retrieval: theoretical modelling

hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorTALEBIESFANDARANI, Somayeh
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorZHAO, Tianjie
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorSHI, Jiancheng
hal.structure.identifierUniversità degli Studi di Roma Tor Vergata [Roma, Italia] = University of Rome Tor Vergata [Rome, Italy] = Université de Rome Tor Vergata [Rome, Italie]
dc.contributor.authorFERRAZZOLI, Paolo
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorZAMANI, Mehdi
hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorPANI, Peejush
dc.date.accessioned2024-04-08T12:04:09Z
dc.date.available2024-04-08T12:04:09Z
dc.date.issued2019
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196295
dc.description.abstractEnMonitoring global vegetation dynamics is of great importance for many environmental applications. The vegetation optical depth (VOD), derived from passive microwave observation, is sensitive to the water content in all aboveground vegetation and could serve as complementary information to optical observations for global vegetation monitoring. The microwave vegetation index (MVI), which is originally derived from the zero-order model, is a potential approach to derive VOD and vegetation water content (VWC), however, it has limited application at dense vegetation in the global scale. In this study, we preferred to use a more complex vegetation model, the Tor Vergata model, which takes into account multi-scattering effects inside the vegetation and between the vegetation and soil layer. Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat. The MVI has been derived through two methods: (i) polarization independent based on model simulations at the L band. Results show that the MVIBT</mml:semantics> has a stronger sensitivity to vegetation properties compared with MVIBP. MVIBT is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that MVIBT has a great potential to retrieve VOD and VWC. By using L band time-series information, the performance of MVIs could be enhanced and its application in a global scale could be improved while paying attention to vegetation structure and saturation effects.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.enmicrowave vegetation index
dc.subject.enTor Vergata model
dc.subject.envegetation optical depth
dc.subject.envegetation water content
dc.title.enMicrowave vegetation index from multi-angular observations and its application in vegetation properties retrieval: theoretical modelling
dc.typeArticle de revue
dc.identifier.doi10.3390/rs11060730
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing
bordeaux.page1-20
bordeaux.volume11
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue6
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02627691
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02627691v1
bordeaux.COinSctx_ver=Z39.88-2004&amp;rft_val_fmt=info:ofi/fmt:kev:mtx:journal&amp;rft.jtitle=Remote%20Sensing&amp;rft.date=2019&amp;rft.volume=11&amp;rft.issue=6&amp;rft.spage=1-20&amp;rft.epage=1-20&amp;rft.eissn=2072-4292&amp;rft.issn=2072-4292&amp;rft.au=TALEBIESFANDARANI,%20Somayeh&amp;ZHAO,%20Tianjie&amp;SHI,%20Jiancheng&amp;FERRAZZOLI,%20Paolo&amp;WIGNERON,%20Jean-Pierre&amp;rft.genre=article


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