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Comparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field

hal.structure.identifierUniversity of Hamburg
dc.contributor.authorMIERNECKI, Maciej
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
hal.structure.identifierUniversitat de València [UV]
dc.contributor.authorLOPEZ-BAEZA, Ernesto
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorKERR, Yann H.
hal.structure.identifierVrije Universiteit Amsterdam [Amsterdam] [VU]
dc.contributor.authorDE JEU, Richard
hal.structure.identifierAtmospheric and Environmental Research, Inc. [AER]
dc.contributor.authorDE LANNOY, Gabrielle
hal.structure.identifierHydrology and Remote Sensing Laboratory
dc.contributor.authorJACKSON, Thomas
hal.structure.identifierAtmospheric and Environmental Research, Inc. [AER]
dc.contributor.authorO'NEILL, Peggy E.
hal.structure.identifierGamma Remote Sensing
hal.structure.identifierSwiss Federal Institute for Forest, Snow and Landscape Research WSL
dc.contributor.authorSCHWANK, Mike
hal.structure.identifierUniversitat de València [UV]
dc.contributor.authorMORAN, Roberto Fernandez
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorBIRCHER, Simone
hal.structure.identifierEuropean Centre for Medium-Range Weather Forecasts [ECMWF]
dc.contributor.authorLAWRENCE, Heather
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorMIALON, Arnaud
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorAHMAD, Al Bitar
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorRICHAUME, Philippe
dc.date.accessioned2024-04-08T12:02:12Z
dc.date.available2024-04-08T12:02:12Z
dc.date.issued2014
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196190
dc.description.abstractEnThe objective of this study was to compare several approaches to soil moisture (SM) retrieval using l-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30°–60°). Based on a three year data set (2010–2012), several SM retrieval approaches developed for spaceborne missions including AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMAP (Soil Moisture Active Passive) and SMOS were compared. The approaches include: the Single Channel Algorithm (SCA) for horizontal (SCA-H) and vertical (SCA-V) polarizations, the Dual Channel Algorithm (DCA), the Land Parameter Retrieval Model (LPRM) and two simplified approaches based on statistical regressions (referred to as ‘Mattar’ and ‘Saleh’). Time series of vegetation indices required for three of the algorithms (SCA-H, SCA-V and ‘Mattar’) were obtained from MODIS observations. The SM retrievals were evaluated against reference SM values estimated from a multiangular 2-Parameter inversion approach. As no in situ SM data was used, the evaluation made here is relative to the use of this specific reference data set. The results obtained with the current base line algorithms developed for SMAP (SCA-H and -V) are in very good agreement with the ‘reference’ SM data set derived from the multi-angular observations (R2 ≈ 0.90, RMSE varying between 0.035 and 0.056 m3/m3 for several retrieval configurations). This result showed that, provided the relationship between vegetation optical depth and a remotely-sensed vegetation index can be calibrated, the SCA algorithms can provide results very close to those obtained from multi-angular observations in this study area. The approaches based on statistical regressions provided similar results and the best accuracy was obtained with the ‘Saleh’ methods based on either bi-angular or bipolarization observations (R2 ≈ 0.93, RMSE ≈ 0.035 m3/m3). The LPRM and DCA algorithms were found to be slightly less successful in retrieving the ‘reference’ SM time series (R2 ≈ 0.75, RMSE ≈ 0.055 m3/m3). However, the two above approaches have the great advantage of not requiring any model calibrations previous to the SM retrievals.
dc.language.isoen
dc.publisherElsevier
dc.subjectSMOS
dc.subjectSoil moisture retrieval
dc.subjectELBARA
dc.subject.enSMAP
dc.subject.enValencia Anchor Station
dc.title.enComparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2014.08.002
dc.subject.halSciences de l'environnement/Milieux et Changements globaux
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
bordeaux.journalRemote Sensing of Environment
bordeaux.page89-101
bordeaux.volume154
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02636614
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02636614v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2014&rft.volume=154&rft.spage=89-101&rft.epage=89-101&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=MIERNECKI,%20Maciej&WIGNERON,%20Jean-Pierre&LOPEZ-BAEZA,%20Ernesto&KERR,%20Yann%20H.&DE%20JEU,%20Richard&rft.genre=article


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