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hal.structure.identifierShihezi University
dc.contributor.authorBAI, Li
hal.structure.identifierShihezi University
dc.contributor.authorLV, Xin
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLI, Xiaojun
dc.date.accessioned2024-04-08T12:03:32Z
dc.date.available2024-04-08T12:03:32Z
dc.date.issued2019
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196273
dc.description.abstractEnA comprehensive evaluation of the performance of satellite-based soil moisture (SM) retrievals is undoubtedly very important to improve its quality and evaluate its potential application in hydrology, climate, and natural disasters (drought, flood, etc.). Since the release of the SMAP (Soil Moisture Active Passive) mission data in April 2015, the associated SM retrieval algorithms have developed rapidly, and their improvement work is still in progress. However, some newly developed SM retrievals have not been fully assessed and inter-compared. One such product is the new multi-temporal dual-channel retrieval algorithm (MT-DCA) SM retrievals, which was recently retrieved using the so-called MT-DCA algorithm. To solve this, we aim to assess the MT-DCA SM retrievals along with the SMAP-enhanced level three SM products (SPL3SMP_E, version 2). More specifically, in this paper we evaluated and inter-compared the two SMAP SM retrievals with the ECMWF (European Centre for Medium-Range Weather Forecasts) modeled SM and ISMN (International Soil Moisture Network) in situ observations by applying four statistical scores: Pearson correlation coefficient (R), root mean square difference (RMSD), bias, and unbiased RMSD (ubRMSD). It was found that both SMAP SM retrievals can better capture the seasonal variations of ECMWF-modeled SM and ground-based measurements according to correlations, and MT-DCA SM was drier than SPL3SMP_E SM by ~0.018 m3/m3 on average on a global scale. With respect to the ISMN ground-based measurements, the performance of SPL3SMP_E SM compared better than the MT-DCA SM. The median ubRMSD of SPL3SMP_E SM and MT-DCA SM with ground measurements computed over all selected ISMN sites were 0.058 m3/m3 and 0.070 m3/m3, respectively.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectsoil moisture
dc.subjectMT-DCA
dc.subjectinter-comparison
dc.subjectLAI
dc.subject.enSMAP
dc.subject.enin situ measurements
dc.subject.enIGBP
dc.title.enEvaluation of two SMAP soil moisture retrievals using modeled- and ground-based measurements
dc.typeArticle de revue
dc.identifier.doi10.3390/rs11242891
dc.subject.halSciences du Vivant [q-bio]
bordeaux.journalRemote Sensing
bordeaux.page1-19
bordeaux.volume11
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue24
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02629309
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02629309v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing&rft.date=2019&rft.volume=11&rft.issue=24&rft.spage=1-19&rft.epage=1-19&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=BAI,%20Li&LV,%20Xin&LI,%20Xiaojun&rft.genre=article


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