Qin Y. auteur aut IRD Ferraz A. auteur aut IRD Mallet C. auteur aut IRD Iovan Corina auteur aut IRD text bookSection eng text/pdf born digital access Timely and accurate measuremen ts of forest parameters are critical for ecosystem studies, sustainable forest resources management, monitoring and planning. This paper presents a processing chain for individual tree segmentation over large areas with airborne LiDAR 3D point cloud and very high resolution (VHR) optical imagery. The proposed processing chain consists of fo rest stand level delineation with optical imagery, individual tree segmentation with Canopy Height Model (CHM) derived from LiDAR point cloud, rough characterization of trees at forest stand level, and point clustering of individual tree with an Adaptive Mean Shift 3D (AMS3D) algorithm. The processing chain is developed with the expectation of supporting operational forest inventory at individual tree level. Experiment is conducted using LiDAR data acquired in Ventoux region, France. Results suggest that the proposed processing chain can be successfully adopted for individual tree characterization over large areas with different forest stands. specialized FRANCE 126 082 800-803 IEEE 2015 International Workshop on the Analysis of Multitemporal Remote Sensing Images, 8., Annecy (FRA), 2015/07/22-24 https://www.documentation.ird.fr/hor/fdi:010067245 978-1-4673-7119-3 [F B010067245] https://www.documentation.ird.fr/hor/fdi:010067245 https://www.documentation.ird.fr/intranet/publi/depot/2016-07-18/010067245.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2016-07-17 2023-02-22 fdi:010067245 fre