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AGU 2015 Fall Meeting, San Francisco, 14 - 18 December 2015 / Anonyme (2015)  

Public Titre : AGU 2015 Fall Meeting, San Francisco, 14 - 18 December 2015 Type de document : Actes de congrès Auteurs : Anonyme, Auteur Editeur : Washington DC [Maryland - Etats-Unis] : American Geophysical Union AGU Année de publication : 2015 Conférence : AGU 2015 Fall Meeting 14/10/2015 18/12/2015 San Francisco Californie - Etats-Unis Langues : Anglais (eng) Numéro de notice : 17335 Affiliation des auteurs : non IGN Nature : Actes DOI : sans En ligne : https://agu.confex.com/agu/fm15/meetingapp.cgi/Home/0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83299

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• Tropical forest structure characterization using airborne lidar data: an individual tree level approach / António Ferraz (dec 2015)  

Tropical forest structure characterization using airborne lidar data: an individual tree level approach / António Ferraz (dec 2015)  

Public contenu dans AGU 2015 Fall Meeting, San Francisco, 14 - 18 December 2015 / Anonyme (2015)   Titre : Tropical forest structure characterization using airborne lidar data: an individual tree level approach Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Victoria Meyer, Auteur Editeur : Washington DC [Maryland - Etats-Unis] : American Geophysical Union AGU Année de publication : dec 2015 Conférence : AGU 2015 Fall Meeting 14/10/2015 18/12/2015 San Francisco Californie - Etats-Unis Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] biomasse aérienne [Termes IGN] distribution spatiale [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt tropicale [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] Panama [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) Fine scale tropical forest structure characterization has been performed by means of field measurements techniques that record both the specie and the diameter at the breast height (dbh) for every tree within a given area. Due to dense and complex vegetation, additional important ecological variables (e.g. the tree height and crown size) are usually not measured because they are hardly recognized from the ground. The poor knowledge on the 3D tropical forest structure has been a major limitation for the understanding of different ecological issues such as the spatial distribution of carbon stocks, regeneration and competition dynamics and light penetration gradient assessments. Airborne laser scanning (ALS) is an active remote sensing technique that provides georeferenced distance measurements between the aircraft and the surface. It provides an unstructured 3D point cloud that is a high-resolution model of the forest. This study presents the first approach for tropical forest characterization at a fine scale using remote sensing data. The multi-modal lidar point cloud is decomposed into 3D clusters that correspond to single trees by means of a technique called Adaptive Mean Shift Segmentation (AMS3D). The ability of the corresponding individual tree metrics (tree height, crown area and crown volume) for the estimation of above ground biomass (agb) over the 50 ha CTFS plot in Barro Colorado Island is here assessed. We conclude that our approach is able to map the agb spatial distribution with an error of nearly 12% (RMSE=28 Mg ha-1) compared with field-based estimates over 1ha plots. Numéro de notice : C2015-033 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/75802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83298