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Mapping soil moisture at a high resolution over mountainous regions by integrating in situ measurements, topography data, and MODIS land surface temperatures

hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierNanjing University of Information Science and Technology [NUIST]
dc.contributor.authorFAN, Lei
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorAL-YAARI, Amen
hal.structure.identifierCentre National d’Etudes Spatiales
hal.structure.identifierGéosciences Environnement Toulouse [GET]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierNicholas School of the Environment
dc.contributor.authorSWENSON, Jennifer
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
dc.contributor.authorXIAO, Qing
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
dc.contributor.authorWEN, Jianguang
hal.structure.identifierChinese Academy of Sciences [CAS]
dc.contributor.authorJIN, Rui
hal.structure.identifierChinese Academy of Sciences [CAS]
dc.contributor.authorKANG, Jian
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLI, Xiaojun
hal.structure.identifierUniversitat de València [UV]
dc.contributor.authorFERNANDEZ-MORAN, R.
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
dc.date.accessioned2024-04-08T12:06:15Z
dc.date.available2024-04-08T12:06:15Z
dc.date.issued2019
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196393
dc.description.abstractEnHydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution. The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy—the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m3/m3, respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m3/m3). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectsoil moisture
dc.subject.enupscaling
dc.subject.enhigh resolution
dc.subject.enBayesian linear regression
dc.subject.enwireless sensor network
dc.subject.entopographic effects
dc.title.enMapping soil moisture at a high resolution over mountainous regions by integrating in situ measurements, topography data, and MODIS land surface temperatures
dc.typeArticle de revue
dc.identifier.doi10.3390/rs11060656
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing
bordeaux.page1-17
bordeaux.volume11
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue6
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02620751
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02620751v1
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=6&rft.spage=1-17&rft.epage=1-17&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=FAN,%20Lei&AL-YAARI,%20Amen&FRAPPART,%20Fr%C3%A9d%C3%A9ric&SWENSON,%20Jennifer&XIAO,%20Qing&rft.genre=article


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