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Seasonal variations in vegetation water content retrieved from microwave remote sensing over Amazon intact forests

hal.structure.identifierCollege of Urban and Environmental Sciences [Beijing]
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorWANG, Huan
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJ.-P., Wigneron
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorCIAIS, Philippe
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorYAO, Yitong
hal.structure.identifierChongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
dc.contributor.authorFAN, Lei
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLIU, Xiangzhuo
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLI, Xiaojun
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierDepartment of Environmental Science, Policy, and Management [Berkeley] [ESPM]
dc.contributor.authorGREEN, Julia
hal.structure.identifierSchool of Remote Sensing and Information Engineering, Wuhan University
dc.contributor.authorTIAN, Feng
hal.structure.identifierCollege of Urban and Environmental Sciences [Beijing]
dc.contributor.authorTAO, Shengli
hal.structure.identifierDepartment of Earth System Science [Beijing] [DESS]
dc.contributor.authorLI, Wei
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierEuropean Centre for Space Applications and Telecommunications [ECSAT]
dc.contributor.authorALBERGEL, Clément
hal.structure.identifierZhengzhou University
dc.contributor.authorWANG, Mengjia
hal.structure.identifierCollege of Urban and Environmental Sciences [Beijing]
dc.contributor.authorLI, Shuangcheng
dc.date.accessioned2024-04-08T11:44:15Z
dc.date.available2024-04-08T11:44:15Z
dc.date.issued2023-02
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195144
dc.description.abstractEnVegetation optical depth (VOD) is seasonally sensitive to plant water content and aboveground biomass. This index has a strong penetrability within the vegetation canopy and is less impacted by atmosphere aerosol contamination effects, clouds and sun illumination than optical vegetation indices. VOD is thus increasingly applied in ecological applications, e.g., carbon stock, phenology and vegetation monitoring. However, VOD retrieval over dense forests is subject to uncertainties caused by the thick canopy and complex multiple scattering effects. Thus, a comprehensive evaluation of VOD products over dense forests is needed for effective and accurate applications. This study evaluated the seasonal variations of eight recently developed/reprocessed VOD products at different frequencies (e.g., Ku-, X-, C- and L-band) over Amazon intact forests, supported by the ORCHIDEE-CAN-NHA model-simulated vegetation water content. Furthermore, we also explored the potential causes of VOD retrieval issues, in terms of retrieval algorithm uncertainties.We first confirmed that soil water availability dominated seasonal dynamics of vegetation water content over Amazon intact forests. This was verified by model-simulated vegetation water content and by C-band radar backscatter observations. Generally, evening or midday vegetation water content shows higher correlations with soil moisture than morning or midnight vegetation water content. In terms of ability of morning or midnight VOD products to follow the seasonality of soil moisture, active microwave ASCAT-IB C-VOD (median seasonal correlation with soil moisture (R) ∼ 0.50) outperforms the passive microwave VOD products, followed by passive microwave AMSR2 X-VOD (R ∼ 0.26) and VODCA X-VOD (R ∼ 0.16). However, SMOS-IC L-VOD (R ∼ −0.15) and AMSR2 C1-VOD (R ∼ −0.20) show obviously negative seasonal correlations with soil moisture across most pixels. This implausible behavior is likely to be caused by the inappropriate setting of time-invariant scattering effects in the passive microwave VOD retrieval algorithms, which could lead to an overestimation of the VOD amplitude during dry seasons. Thus, we recommend that the seasonal scattering effects be considered in the passive microwave VOD retrieval algorithms. These findings can contribute to the improvement of VOD retrieval algorithms and help with the development of their ecological applications over Amazon dense forests.
dc.language.isoen
dc.publisherElsevier
dc.subject.enVegetation optical depth
dc.subject.enVegetation water content
dc.subject.enseasonality
dc.subject.enAmazon forest
dc.subject.enORCHIDEE-CAN-NHA land surface model
dc.subject.enSMOS-IC
dc.subject.enASCAT-IB
dc.subject.enAMSR2
dc.subject.enVODCA
dc.title.enSeasonal variations in vegetation water content retrieved from microwave remote sensing over Amazon intact forests
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2022.113409
dc.subject.halPlanète et Univers [physics]
bordeaux.journalRemote Sensing of Environment
bordeaux.page113409
bordeaux.volume285
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04095055
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04095055v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2023-02&rft.volume=285&rft.spage=113409&rft.epage=113409&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=WANG,%20Huan&J.-P.,%20Wigneron&CIAIS,%20Philippe&YAO,%20Yitong&FAN,%20Lei&rft.genre=article


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