Modeling directional anisotropy of thermal infrared measurements over a pine forest canopy

Kurz Britta, Lagouarde Jean-Pierre, Moreau Patrick, Guyon Dominique, Champion Isabelle, Ogée Jérôme, Boudon Frédéric, Caraglio Yves, Godin Christophe, Pradal Christophe. 2006. Modeling directional anisotropy of thermal infrared measurements over a pine forest canopy. In : Second recent advances in quantitative remote sensing (RAQRS'II), Auditori de Torrent, Spain, 25-29 September 2006. Sobrino José A. (ed.). Universidad de Valencia. Valence : Universitat de Valencia, 320-325. ISBN 978-84-370-6533-5 International Symposium on Recent Advances in Quantitative Remote Sensing. 2, Valence, Espagne, 25 Septembre 2006/29 Septembre 2006.

Résumé : Experimental airborne thermal infrared (TIR) measurements performed over a maritime pine stand in the Landes forest in the southwest of France revealed important hot spot effects and directional anisotropy reaching up to ±2 K in summer conditions. The generalization of such results requires modelling efforts with the scope of different practical applications such as eventual angular correction of large swath satellite data, or assimilation of TIR data in forest growth models. The directional TIR anisotropy model is based on a 3D structural modelling of pine canopies combined with a ray tracing program (POV-ray). The images generated in a given viewing configuration are used to derive the percentages of sunlit and shadowed elements of the canopy; the resulting directional temperature is then computed by weighing their elementary temperatures. In a first step the 3D canopy model itself is validated against gap frequency measurements. The TIR anisotropy modelling approach is validated in a second step prescribing elementary temperatures from ground based measurements and comparing derived directional temperature against airborne data. Finally the coupling with a forest soil-vegetation model MuSICA developed at the laboratory providing the elementary temperatures at different levels inside the canopy and the possibilities opened for assimilating actual TIR satellite data are discussed.

Classification Agris : U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F62 - Physiologie végétale - Croissance et développement
K10 - Production forestière

Auteurs et affiliations

• Kurz Britta, INRA (FRA)
• Lagouarde Jean-Pierre, INRA (FRA)
• Moreau Patrick, INRA (FRA)
• Guyon Dominique, INRA (FRA)
• Champion Isabelle, INRA (FRA)
• Ogée Jérôme, INRA (FRA)
• Boudon Frédéric, CIRAD-AMIS-UMR AMAP (FRA) ORCID: 0000-0001-9636-3102
• Caraglio Yves, CIRAD-AMIS-UMR AMAP (FRA)
• Godin Christophe, CIRAD-AMIS-UMR AMAP (FRA)
• Pradal Christophe, CIRAD-AMIS-UMR AMAP (FRA) ORCID: 0000-0002-2555-761X

Source : Cirad - Agritrop (https://agritrop.cirad.fr/555928/)

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