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An analytical four-component directional brightness temperature model for crop and forest canopies

hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
hal.structure.identifierJoint Center for Global Change Studies
hal.structure.identifierCollege of Resources and Environment
dc.contributor.authorBIAN, Zunjian
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorCAO, Biao
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorLI, Hua
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorDU, Yongming
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLAGOUARDE, Jean-Pierre
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
dc.contributor.authorXIAO, Qing
hal.structure.identifierState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
hal.structure.identifierJoint Center for Global Change Studies
hal.structure.identifierCollege of Resources and Environment
dc.contributor.authorLIU, Qinhuo
dc.date.accessioned2024-04-08T12:05:21Z
dc.date.available2024-04-08T12:05:21Z
dc.date.issued2018
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196352
dc.description.abstractEnMeasurements of surface thermal infrared (TIR) radiance that are made to extract temperatures display strong directional anisotropy effects. Directional brightness temperature (BT) models that describe this anisotropic behavior of TIR emissions can be applied to separate component temperatures using multi-angle observations. The surface temperature differences that occur between sunlit and shaded areas and the leaf clumping phenomenon jointly affect the directional signatures of out-of-canopy directional BTs. However, these factors are not fully considered in existing directional BT models. This paper therefore extends the FR97 analytical model to 1) a four-component scene containing sunlit and shaded soil and leaves by incorporating the effective emissivity values of the sunlit and shaded parts and 2) row-planted crop and forest canopies by introducing a leaf clumping index. The proposed model was assessed using a synthetic dataset that was generated by the Thermal Radiosity-Graphics Combined Model (TRGM) under various conditions. The evaluation results indicated that the proposed model performed as well as the Scattering by Arbitrarily Inclined Leaves (4SAIL) model over continuous canopies with root mean squared errors (RMSEs) lower than 0.3 degrees C. Over non-continuous crops and forests, the behavior of the proposed model displayed improved agreement with the TRGM with RMSEs lower than 0.65 degrees C. The proposed model also displayed a robust performance over both the maize and pine canopies, which was evaluated against the directional anisotropy of measured datasets that were collected at the Huailai remote sensing test site and the Institut National de la Recherche Agronomique (INRA), respectively. From these points, the proposed model has potential for component temperature inversion and rapid assessment of TIR angular effects.
dc.language.isoen
dc.publisherElsevier
dc.subject.endirectional brightness temperature model
dc.subject.enFR97
dc.subject.endirectional anisotropy
dc.subject.enleaf clumping index
dc.title.enAn analytical four-component directional brightness temperature model for crop and forest canopies
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2018.03.010
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing of Environment
bordeaux.page731-746
bordeaux.volume209
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02623356
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02623356v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2018&rft.volume=209&rft.spage=731-746&rft.epage=731-746&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=BIAN,%20Zunjian&CAO,%20Biao&LI,%20Hua&DU,%20Yongming&LAGOUARDE,%20Jean-Pierre&rft.genre=article


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