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

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
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorKERR, Yann H.
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorRODRIGUEZ‐FERNANDEZ, Nemesio
hal.structure.identifierNASA Goddard Space Flight Center [GSFC]
dc.contributor.authorO'NEILL, Peggy
hal.structure.identifierHydrology and Remote Sensing Laboratory
dc.contributor.authorJACKSON, Thomas
hal.structure.identifierNASA Goddard Space Flight Center [GSFC]
dc.contributor.authorDE LANNOY, Gabrielle
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.authorMIALON, Arnaud
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorRICHAUME, Philippe
hal.structure.identifierJet Propulsion Laboratory [JPL]
dc.contributor.authorYUEH, Simon
dc.date.accessioned2024-04-08T11:58:20Z
dc.date.available2024-04-08T11:58:20Z
dc.date.issued2016
dc.date.conference2016-07-10
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195922
dc.description.abstractEnIn this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA's Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA's Soil Moisture and Ocean Salinity (SMOS) satellite retrieved surface soil moisture. This was achieved by calibrating coefficients of the regression model using SMOS soil moisture and horizontal and vertical brightness temperatures (TB), over the 2013 — 2014 period. Next, this model was applied to recent SMAP TB data from 31/03/2015–08/09/2015. The retrieved surface soil moisture from SMAP (referred here to as SMAP-reg) was compared to the operational SMAP L3 surface soil moisture retrieved using the single channel algorithm. Both exhibit comparable temporal dynamics with a good agreement of correlation (correlation coefficient R mostly > 0.8) between the SMAP-reg and the operational SMAP L3 surface soil moisture products.
dc.language.isoen
dc.publisherIEEE
dc.source.titleIEEE International Geoscience and Remote Sensing Symposium Proceedings
dc.subjectsoil moisture
dc.subjectSMOS
dc.subject.enSMAP
dc.subject.enstatistical regression
dc.title.enFirst application of regression analysis to retrieve soil moisture from SMAP brightness temperature observations consistent with SMOS
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/IGARSS.2016.7729417
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
dc.subject.halPlanète et Univers [physics]/Sciences de la Terre
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.conference.titleIGARSS 2016 Advancing the understanding of our living planet
bordeaux.countryCN
bordeaux.title.proceedingIEEE International Geoscience and Remote Sensing Symposium Proceedings
bordeaux.conference.cityPékin
bordeaux.peerReviewednon
hal.identifierhal-02743418
hal.version1
hal.invitednon
hal.conference.organizerIEEE Geoscience and Remote Sensing Society (GRSS). USA.
hal.conference.end2016-07-15
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02743418v1
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