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First application of regression analysis to retrieve soil moisture from SMAP brightness temperature observations consistent with SMOS soil moisture

hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorAL YAARI, Amen
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
dc.contributor.authorKERR, Yann H.
dc.contributor.authorRODRIGUEZ‐FERNANDEZ, Nemesio
hal.structure.identifierDepartment of Earth and Environmental Sciences [Leuven] [EES]
dc.contributor.authorO'NEILL, Peggy
hal.structure.identifierUnited States Department of Agriculture
dc.contributor.authorJACKSON, Thomas
hal.structure.identifierDepartment of Earth and Environmental Sciences [Leuven] [EES]
dc.contributor.authorDE LANNOY, Gabrielle
dc.contributor.authorAHMAD, Al Bitar
dc.contributor.authorMIALON, Arnaud
dc.contributor.authorRICHAUME, Philippe
hal.structure.identifierJet Propulsion Laboratory [JPL]
dc.contributor.authorYUEH, Simon
dc.date.accessioned2024-04-08T12:10:37Z
dc.date.available2024-04-08T12:10:37Z
dc.date.issued2016
dc.date.conference2016-04-11
dc.identifier.isbn978-952-60-6744-5 (printed) - 978-952-60-6743-8 (pdf)
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196643
dc.description.abstractEnTwo dedicated soil moisture (SM) spaceborne missions, ESA’s Soil Moisture and Ocean Salinity (SMOS) and NASA’s Soil Moisture Active Passive (SMAP) satellites, were launched in 2009 and 2015, respectively. Both satellites have been providing microwave brightness temperature (TB) observations and SM retrievals at L-band since then (Entekhabi et al., 2010; Kerr et al., 2012). A recent study demonstrated the efficiency of physically-based multiple-linear regression equations (Wigneron et al., 2004) to retrieve SM from AMSR-E TB observations. The regression equations were derived analytically from the radiative transfer model. The purpose of that initial study was to extend the SMOS SM product into the past i.e., 2003-2009, using AMSR-E TB observations. The current study follows the same strategy to retrieve SM from SMAP TB observations with a purpose to extend the SMOS SM product into the future at the global scale. Regression coefficients were calibrated using SMOS horizontal and vertical TB observations and SM level 3 (SMOSL3 as a training data), over the 2013 - 2014 period. Based on these calibrated coefficients, global SM maps were produced from the SMAP TB observations during the 31/03-08/09/2015 period (referred here to as SMAP-reg). The SM data set obtained from SMAP TBs using the regression equations has been compared to the SMAP SM dataset computed withthe single channel algorithm and both exhibit the same temporal dynamics. For instance, figure 1 shows the (Pearson) correlation coefficient (R) between SMAP-reg and SMAP original SM over 31/03-08/09/2015. A remarkable agreement, R (mostly > 0.8), was obtained between the SMAP-reg and SMAP original SM products.Ongoing evaluations of the SMAP-reg SM product, with comparison to the SMAP original SM, against the global MERRA-Land SM simulations and in situ measurements will be presented. The main interest in the SMAP-reg SM product is that it is fully consistent with the SMOS Level 3 SM product. One of the key remaining tasks is toensure the consistent relative calibration between SMOS and SMAP TBs.
dc.language.isoen
dc.publisherAalto University publication series
dc.publisher.location(finland)
dc.subjectprojet smos
dc.subjecttélédétection
dc.subjectdonnée satellite
dc.subjectéquation de régression
dc.subjectmodèle de transfert radiatif
dc.subject.enremote sensing
dc.title.enFirst application of regression analysis to retrieve soil moisture from SMAP brightness temperature observations consistent with SMOS soil moisture
dc.typeAutre communication scientifique (congrès sans actes - poster - séminaire...)
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
bordeaux.pagenp
bordeaux.volume4
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.conference.titleMicroRad 2016 - 14. Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment
bordeaux.countryFI
bordeaux.conference.cityEspoo
bordeaux.peerReviewedoui
hal.identifierhal-01594464
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2016-04-14
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01594464v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2016&rft.volume=4&rft.spage=np&rft.epage=np&rft.au=AL%20YAARI,%20Amen&WIGNERON,%20Jean-Pierre&KERR,%20Yann%20H.&RODRIGUEZ%E2%80%90FERNANDEZ,%20Nemesio&O'NEILL,%20Peggy&rft.isbn=978-952-60-6744-5%20(printed)%20-%20978-952-60-6743-8%20(pdf)&rft.genre=conference


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