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A semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices

hal.structure.identifierChinese Academy of Sciences [CAS]
hal.structure.identifierCollege of Resources and Environment
dc.contributor.authorBIAN, Zunjian
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorROUJEAN, Jean-Louis
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLAGOUARDE, Jean-Pierre
hal.structure.identifierChinese Academy of Sciences [CAS]
dc.contributor.authorCAO, Biao
hal.structure.identifierChinese Academy of Sciences [CAS]
dc.contributor.authorLI, Hua
hal.structure.identifierChinese Academy of Sciences [CAS]
dc.contributor.authorDU, Yongming
hal.structure.identifierCollege of Global Change and Earth System Science [GCESS]
dc.contributor.authorLIU, Qiang
hal.structure.identifierChinese Academy of Sciences [CAS]
hal.structure.identifierCollege of Resources and Environment
dc.contributor.authorXIAO, Qing
hal.structure.identifierChinese Academy of Sciences [CAS]
hal.structure.identifierCollege of Resources and Environment
dc.contributor.authorLIU, Qinhuo
dc.date.accessioned2024-04-08T12:06:00Z
dc.date.available2024-04-08T12:06:00Z
dc.date.issued2020
dc.identifier.issn0924-2716
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196384
dc.description.abstractEnMeasurements of the surface thermal infrared (TIR) radiance provides an estimate of the land surface temperature (LST). However, any TIR measurement must be acquired under a certain geometry observation, which may refer to strong directional anisotropies. Although physical radiative transfer models can provide high precision directional brightness temperature simulation, they are too complex for processing large volumes of satellite data. With the objective to compare TIR measures acquired under different viewing angles, the topic of angular normalization issue for retrieved LSTs could be treated based on semi-empirical modelling. In this paper, we consider such category of models to simulate the directional anisotropy of surface brightness temperatures in combination with visible and near-infrared (VNIR) data. In these models, the vegetation fraction and the hot spot effect are depicted by a vegetation index and a brightness factor, respectively. An evaluation of the method is performed with both synthetic and measured datasets. The directional anisotropies that are fitted by this semi-empirical model demonstrate good agreement with an extensive synthetic dataset that is generated with the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) soil-vegetation-atmosphere transfer model. An evaluation using airborne multi-angle TIR data also reveals that this model performs well when predicting BT directional anisotropies, with root mean square errors (RMSEs) of less than 0.31 °C over a maize-planted area. Relative to Roujean-Lagouarde (RL) and Vinnikov models using only TIR data, the proposed model offers better performances. In addition, for future use with satellite data, the proposed model using observations at different times and the combination with VNIR BRDF model are also evaluated, and good results are obtained. It yields a promising approach for the angular normalization of LST and mosaics of fine-scale images.
dc.language.isoen
dc.publisherElsevier
dc.subject.endirectional brightness temperature
dc.subject.enVNIR and TIR data
dc.subject.enangular normalization
dc.title.enA semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices
dc.typeArticle de revue
dc.identifier.doi10.1016/j.isprsjprs.2019.12.004
dc.subject.halSciences du Vivant [q-bio]
bordeaux.journalISPRS Journal of Photogrammetry and Remote Sensing
bordeaux.page136-148
bordeaux.volume160
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02621422
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02621422v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=ISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing&rft.date=2020&rft.volume=160&rft.spage=136-148&rft.epage=136-148&rft.eissn=0924-2716&rft.issn=0924-2716&rft.au=BIAN,%20Zunjian&ROUJEAN,%20Jean-Louis&LAGOUARDE,%20Jean-Pierre&CAO,%20Biao&LI,%20Hua&rft.genre=article


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