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Forests 2016, 7(6), 127; doi:10.3390/f7060127

Forest Inventory with Terrestrial LiDAR: A Comparison of Static and Hand-Held Mobile Laser Scanning

1
TERRA Research Unit, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, Gembloux 5030, Belgium
2
Laboratory of Geo-information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, Wageningen 6708 PB, The Netherlands
3
Earth Observations, Climate and Optical Group, National Physical Laboratory, Hampton Road, Teddington, Middlesex TW11 0LW, UK
4
Department of Geography, University College London, Gower Street, London WC1E 6BT, UK
5
BIOSE Research Unit, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, Gembloux 5030, Belgium
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Academic Editors: Juha Hyyppä, Xinlian Liang and Eetu Puttonen
Received: 16 April 2016 / Revised: 1 June 2016 / Accepted: 6 June 2016 / Published: 21 June 2016
(This article belongs to the Special Issue Forest Ground Observations through Terrestrial Point Clouds)
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Abstract

The application of static terrestrial laser scanning (TLS) in forest inventories is becoming more effective. Nevertheless, the occlusion effect is still limiting the processing efficiency to extract forest attributes. The use of a mobile laser scanner (MLS) would reduce this occlusion. In this study, we assessed and compared a hand-held mobile laser scanner (HMLS) with two TLS approaches (single scan: SS, and multi scan: MS) for the estimation of several forest parameters in a wide range of forest types and structures. We found that SS is competitive to extract the ground surface of forest plots, while MS gives the best result to describe the upper part of the canopy. The whole cross-section at 1.3 m height is scanned for 91% of the trees (DBH > 10 cm) with the HMLS leading to the best results for DBH estimates (bias of −0.08 cm and RMSE of 1.11 cm), compared to no fully-scanned trees for SS and 42% fully-scanned trees for MS. Irregularities, such as bark roughness and non-circular cross-section may explain the negative bias encountered for all of the scanning approaches. The success of using MLS in forests will allow for 3D structure acquisition on a larger scale and in a time-efficient manner. View Full-Text
Keywords: forestry; terrestrial laser scanning; hand-held mobile laser scanning; HMLS; TLS; SLAM; digital elevation model; stem mapping forestry; terrestrial laser scanning; hand-held mobile laser scanning; HMLS; TLS; SLAM; digital elevation model; stem mapping
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bauwens, S.; Bartholomeus, H.; Calders, K.; Lejeune, P. Forest Inventory with Terrestrial LiDAR: A Comparison of Static and Hand-Held Mobile Laser Scanning. Forests 2016, 7, 127.

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