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Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests

BACKGROUND AND AIMS: In addition to terrestrial laser scanning (TLS), mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3-D data for various applications in forest research. Using mobile platforms, the 3-D recording of large forest areas is carried...

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Autores principales: Bienert, Anne, Georgi, Louis, Kunz, Matthias, von Oheimb, Goddert, Maas, Hans-Gerd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557376/
https://www.ncbi.nlm.nih.gov/pubmed/34232276
http://dx.doi.org/10.1093/aob/mcab087
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author Bienert, Anne
Georgi, Louis
Kunz, Matthias
von Oheimb, Goddert
Maas, Hans-Gerd
author_facet Bienert, Anne
Georgi, Louis
Kunz, Matthias
von Oheimb, Goddert
Maas, Hans-Gerd
author_sort Bienert, Anne
collection PubMed
description BACKGROUND AND AIMS: In addition to terrestrial laser scanning (TLS), mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3-D data for various applications in forest research. Using mobile platforms, the 3-D recording of large forest areas is carried out within a short space of time. Vegetation structure is described by millions of 3-D points which show an accuracy in the millimetre range and offer a powerful basis for automated vegetation modelling. The successful extraction of single trees from the point cloud is essential for further evaluations and modelling at the individual-tree level, such as volume determination, quantitative structure modelling or local neighbourhood analyses. However, high-precision automated tree segmentation is challenging, and has so far mostly been performed using elaborate interactive segmentation methods. METHODS: Here, we present a novel segmentation algorithm to automatically segment trees in MLS point clouds, applying distance adaptivity as a function of trajectory. In addition, tree parameters are determined simultaneously. In our validation study, we used a total of 825 trees from ten sample plots to compare the data of trees segmented from MLS data with manual inventory parameters and parameters derived from semi-automatic TLS segmentation. KEY RESULTS: The tree detection rate reached 96 % on average for trees with distances up to 45 m from the trajectory. Trees were almost completely segmented up to a distance of about 30 m from the MLS trajectory. The accuracy of tree parameters was similar for MLS-segmented and TLS-segmented trees. CONCLUSIONS: Besides plot characteristics, the detection rate of trees in MLS data strongly depends on the distance to the travelled track. The algorithm presented here facilitates the acquisition of important tree parameters from MLS data, as an area-wide automated derivation can be accomplished in a very short time.
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spelling pubmed-85573762021-11-01 Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests Bienert, Anne Georgi, Louis Kunz, Matthias von Oheimb, Goddert Maas, Hans-Gerd Ann Bot Original Articles BACKGROUND AND AIMS: In addition to terrestrial laser scanning (TLS), mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3-D data for various applications in forest research. Using mobile platforms, the 3-D recording of large forest areas is carried out within a short space of time. Vegetation structure is described by millions of 3-D points which show an accuracy in the millimetre range and offer a powerful basis for automated vegetation modelling. The successful extraction of single trees from the point cloud is essential for further evaluations and modelling at the individual-tree level, such as volume determination, quantitative structure modelling or local neighbourhood analyses. However, high-precision automated tree segmentation is challenging, and has so far mostly been performed using elaborate interactive segmentation methods. METHODS: Here, we present a novel segmentation algorithm to automatically segment trees in MLS point clouds, applying distance adaptivity as a function of trajectory. In addition, tree parameters are determined simultaneously. In our validation study, we used a total of 825 trees from ten sample plots to compare the data of trees segmented from MLS data with manual inventory parameters and parameters derived from semi-automatic TLS segmentation. KEY RESULTS: The tree detection rate reached 96 % on average for trees with distances up to 45 m from the trajectory. Trees were almost completely segmented up to a distance of about 30 m from the MLS trajectory. The accuracy of tree parameters was similar for MLS-segmented and TLS-segmented trees. CONCLUSIONS: Besides plot characteristics, the detection rate of trees in MLS data strongly depends on the distance to the travelled track. The algorithm presented here facilitates the acquisition of important tree parameters from MLS data, as an area-wide automated derivation can be accomplished in a very short time. Oxford University Press 2021-07-07 /pmc/articles/PMC8557376/ /pubmed/34232276 http://dx.doi.org/10.1093/aob/mcab087 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Annals of Botany Company. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Bienert, Anne
Georgi, Louis
Kunz, Matthias
von Oheimb, Goddert
Maas, Hans-Gerd
Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title_full Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title_fullStr Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title_full_unstemmed Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title_short Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
title_sort automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557376/
https://www.ncbi.nlm.nih.gov/pubmed/34232276
http://dx.doi.org/10.1093/aob/mcab087
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