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Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization / B. Koetz in Remote sensing of environment, vol 106 n° 4 (28/02/2007)  

Public [article]  inRemote sensing of environment > vol 106 n° 4 (28/02/2007) . - pp 449 - 459 Titre : Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization Type de document : Article/Communication Auteurs : B. Koetz, Auteur ; G. Sun, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 449 - 459 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] canopée [Termes IGN] données lidar [Termes IGN] estimation statistique [Termes IGN] forêt [Termes IGN] fusion de données [Termes IGN] hauteur des arbres [Termes IGN] lasergrammétrie [Termes IGN] Leaf Area Index [Termes IGN] méthode robuste [Termes IGN] modèle de transfert radiatif [Termes IGN] modèle numérique de surface [Termes IGN] spectrométrie Résumé : (Auteur) A comprehensive canopy characterization of forests is derived from the combined remote sensing signal of imaging spectrometry and large footprint LIDAR. The inversion of two linked physically based Radiative Transfer Models (RTM) provided the platform for synergistically exploiting the specific and independent information dimensions obtained by the two earth observation systems. Due to its measurement principle, LIght Detection And Ranging (LIDAR) is particularly suited to assess the horizontal and vertical canopy structure of forests, while the spectral measurements of imaging spectrometry are specifically rich on information for biophysical and -chemical canopy properties. In the presented approach, the specific information content inherent to the observations of the respective sensor was not only able to complement the canopy characterization, but also helped to solve the ill-posed problem of the RTM inversion. The theoretical feasibility of the proposed earth observation concept has been tested on a synthetic data set generated by a forest growth model for a wide range of forest stands. Robust estimates on forest canopy characteristics were achieved, ranging from maximal tree height, fractional cover (fcover), Leaf Area Index (LAI) to the foliage chlorophyll and water content. The introduction of prior information on the canopy structure derived from large footprint LIDAR observations significantly improved the retrieval performance relative to estimates based solely on spectral information. Copyright Elsevier Numéro de notice : A2007-069 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.09.013 En ligne : https://doi.org/10.1016/j.rse.2006.09.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28434 [article]