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MASSIVE-SCALE TREE MODELLING FROM TLS DATA

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Other literature type , Journal 11 Mar 2015 Netherlands Publisher:Copernicus GmbHJournal:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, volume II-3/W4, pages 189-196 (eissn: 2194-9050,

Authors: Raumonen, P.; Casella, E.; Calders, K.; Murphy, S.; Åkerblom, M.; Kaasalainen, M.;

doi: 10.5194/isprsannals-ii-3-w4-189-2015

MASSIVE-SCALE TREE MODELLING FROM TLS DATA

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Abstract

Abstract. This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak plot and a 80-m diameter Australian eucalyptus plot. For the oak plot the total biomass was overestimated by about 17 %, when compared to allometry (N = 15), and the modelling time was about 100 min with a laptop. For the eucalyptus plot the total biomass was overestimated by about 8.5 %, when compared to a destructive reference (N = 27), and the modelling time was about 160 min. The method provides accurate and fast tree modelling abilities for, e.g., biomass estimation and ground truth data for airborne measurements at a massive ground scale.

Country

Netherlands

Related Organizations

Tampere University
Finland
University of Melbourne
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Tampereen teknillinen yliopisto
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Université Wageningen
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Tampere University of Technology
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Keywords

Technology, LiDAR, Forest plot, Ground truth, Quantitative structure models, Laboratory of Geo-information Science and Remote Sensing, Applied optics. Photonics, Laboratorium voor Geo-informatiekunde en remote sensing, Laboratorium voor Geo-informatiekunde en Remote Sensing, Biomass, Automatic tree extraction, Eucalyptus, T, Engineering (General). Civil engineering (General), PE&RC, TA1501-1820, Oak, TA1-2040

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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%