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hal.structure.identifierDepartment of Remote Sensing and GIS
dc.contributor.authorKHANDAN, Reza
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJ.-P., Wigneron
hal.structure.identifierDepartment of Civil and Environmental Engineering of the University of Perugia, Italy
dc.contributor.authorBONAFONI, Stefania
hal.structure.identifierAlabama State University
dc.contributor.authorBIAZAR, Arastoo Pour
hal.structure.identifierIslamic Azad University
dc.contributor.authorGHOLAMNIA, Mehdi
dc.date.accessioned2024-04-08T11:48:10Z
dc.date.available2024-04-08T11:48:10Z
dc.date.issued2022-02-07
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195307
dc.description.abstractEnThe correction of Soil Moisture (SM) estimates in Land Surface Models (LSMs) is considered essential for improving the performance of numerical weather forecasting and hydrologic models used in weather and climate studies. Along with surface screen-level variables, the satellite data, including Brightness Temperature (BT) from passive microwave sensors, and retrieved SM from active, passive, or combined active-passive sensor products have been used as two critical inputs in improvements of the LSM. The present study reviewed the current status in correcting LSM SM estimates, evaluating the results with in situ measurements. Based on findings from previous studies, a detailed analysis of related issues in the assimilation of SM in LSM, including bias correction of satellite data, applied LSMs and in situ observations, input data from various satellite sensors, sources of errors, calibration (both LSM and radiative transfer model), are discussed. Moreover, assimilation approaches are compared, and considerations for assimilation implementation are presented. A quantitative representation of results from the literature review, including ranges and variability of improvements in LSMs due to assimilation, are analyzed for both surface and root zone SM. A direction for future studies is then presented.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.enM Soil Moisture (SM)
dc.subject.enassimilation
dc.subject.enLand Surface Model (LSM)
dc.subject.enRadiative Transfer Model (RTM)
dc.subject.ensurface
dc.subject.enroot zone
dc.title.enAssimilation of Satellite-Derived Soil Moisture and Brightness Temperature in Land Surface Models: A Review
dc.typeArticle de revue
dc.identifier.doi10.3390/rs14030770
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing
bordeaux.page770
bordeaux.volume14
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue3
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-03609946
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03609946v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing&rft.date=2022-02-07&rft.volume=14&rft.issue=3&rft.spage=770&rft.epage=770&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=KHANDAN,%20Reza&J.-P.,%20Wigneron&BONAFONI,%20Stefania&BIAZAR,%20Arastoo%20Pour&GHOLAMNIA,%20Mehdi&rft.genre=article


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