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Breast height diameter estimation from high-density airborne LiDAR data

Bucksch, Alexander and Lindenbergh, Roderik C. and Abd. Rahman, Muhammad Zulkarnain and Menenti, Massimo (2014) Breast height diameter estimation from high-density airborne LiDAR data. IEEE Geoscience and Remote Sensing Letters, 11 (6). pp. 1056-1060. ISSN 1545-598X

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Official URL: http://dx.doi.org/10.1109/LGRS.2013.2285471

Abstract

High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The estimates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.

Item Type:Article
Uncontrolled Keywords:computational geometry, forestry, image analysis
Subjects:H Social Sciences > HD Industries. Land use. Labor
Divisions:Geoinformation and Real Estate
ID Code:52036
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:01 Feb 2016 11:53
Last Modified:30 Nov 2018 15:00

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