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A two parameter model to simulate thermal infrared directional effects for remote sensing applications

hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorDUFFOUR, Clément
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLAGOUARDE, Jean-Pierre
hal.structure.identifierCentre national de recherches météorologiques [CNRM]
dc.contributor.authorROUJEAN, Jean-Louis
dc.date.accessioned2024-04-08T12:11:43Z
dc.date.available2024-04-08T12:11:43Z
dc.date.issued2017
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196705
dc.description.abstractEnMeasurements of land surface temperature (LST) performed in the thermal infrared (TIR) domain are prone to strong directional anisotropy. Instead of detailed analytical physical TIR models requiring too much input information and computational capacities, simplified parametric approaches capable to mimic and correct with precision the angular effects on LST will be deemed suitable for practical satellite applications. In this study, we present a simple two parameters model, so-called RL (Roujean-Lagouarde), which shows capabilities to properly depict the directional signatures of both urban and vegetation targets within an accuracy better than 1 °C. This latter value is the RMSE (root mean square error) obtained as the best adjustment of the RL model against in situ datasets. Then the RL approach was compared to a synthetic dataset generated by the model Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) in which large variability in meteorological scenarios, canopy structure and water status conditions was accounted for. Results indicate RMSE ≤ 0.6 °C which is a very hopeful result. Besides, the RL model performs even better than the popular parametric model of Vinnikov that encompasses two unknowns. The ability of RL model to better reproduce the hotspot phenomenon explains this feature. The RL model appears as a potential candidate for future operational processing chains of TIR satellite data because it fulfills the requirements of both simple analytical formulation and limited number of input parameters. Efforts nevertheless remain to be done on inversion methodologies.
dc.language.isoen
dc.publisherElsevier
dc.rights.urihttp://creativecommons.org/licenses/by-sa/
dc.subjecttélédétection infrarouge
dc.subjectdonnée satellite
dc.subjectanisotropie directionnelle
dc.subject.endirectional anisotropy
dc.subject.enland surface temperature
dc.subject.enthermal infrared (TIR) remote sensing
dc.subject.enparametric model
dc.subject.enSCOPE
dc.title.enA two parameter model to simulate thermal infrared directional effects for remote sensing applications
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2016.08.012
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
bordeaux.journalRemote Sensing of Environment
bordeaux.page250-261
bordeaux.volume186
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-01511398
hal.version1
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01511398v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2017&rft.volume=186&rft.spage=250-261&rft.epage=250-261&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=DUFFOUR,%20Cl%C3%A9ment&LAGOUARDE,%20Jean-Pierre&ROUJEAN,%20Jean-Louis&rft.genre=article


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