globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2014.05.001
Scopus记录号: 2-s2.0-84904733383
论文题名:
PTrees: A point-based approach to forest tree extractionfrom lidar data
作者: Vega C; , Hamrouni A; , El Mokhtari A; , Morel M; , Bock J; , Renaud J; -P; , Bouvier M; , Durrieue S
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 33, 期:1
起始页码: 98
结束页码: 108
语种: 英语
英文关键词: Dynamic segmentation ; Forest inventory ; Lidar ; Point cloud normalization ; Point cloud processing ; Tree crown extraction
Scopus关键词: forest inventory ; image analysis ; lidar ; pattern recognition ; remote sensing ; segmentation
英文摘要: This paper introduces PTrees, a multi-scale dynamic point cloud segmentation dedicated to forest tree extraction from lidar point clouds. The method process the point data using the raw elevation values (Z) and compute height (H = Z - ground elevation) during post-processing using an innovative procedure allowing to preserve the geometry of crown points. Multiple segmentations are done at different scales. Segmentation criteria are then applied to dynamically select the best set of apices from the tree segment sextracted at the various scales. The selected set of apices is then used to generate a final segmentation. PTrees has been tested in 3 different forest types, allowing to detect 82% of the trees with under 10% of false detection rate. Future development will integrate crown profile estimation during the segmentation process in order to both maximize the detection of suppressed trees and minimize false detections. © 2014 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79745
Appears in Collections:气候变化事实与影响

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作者单位: Institut Français de Pondichéry, 11 Saint-Louis Street, Pondicherry 605 001, India; Institut National de l'Information Géographique et Forestière, Laboratoire de l'Inventaire Forestier, 11 rue de l'Ile de Corse, 54000 Nancy, France; Office National des Forêts, 42 quai Charles Roissard, 73023 Chambéry Cedex, France; Office National des Forêts, 11 rue Ile de Corse, 54000 Nancy, France; UMR TETIS IRSTEA, 500 rue J.F. Breton BP 5095, 34196 Montpellier Cedex 05, France

Recommended Citation:
Vega C,, Hamrouni A,, El Mokhtari A,et al. PTrees: A point-based approach to forest tree extractionfrom lidar data[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,33(1)
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