Analysing individual 3D tree structure using the R package ITSMe
Abstract Detailed 3D quantification of tree structure plays a crucial role in understanding tree‐ and plot‐level biophysical processes. Light detection and ranging (LiDAR) has led to a revolution in tree structural measurements and its 3D data are increasingly becoming publicly available. Yet, calcu...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Methods in Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/2041-210X.14026 |
| _version_ | 1827888336643031040 |
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| author | Louise Terryn Kim Calders Markku Åkerblom Harm Bartholomeus Mathias Disney Shaun Levick Niall Origo Pasi Raumonen Hans Verbeeck |
| author_facet | Louise Terryn Kim Calders Markku Åkerblom Harm Bartholomeus Mathias Disney Shaun Levick Niall Origo Pasi Raumonen Hans Verbeeck |
| author_sort | Louise Terryn |
| collection | DOAJ |
| description | Abstract Detailed 3D quantification of tree structure plays a crucial role in understanding tree‐ and plot‐level biophysical processes. Light detection and ranging (LiDAR) has led to a revolution in tree structural measurements and its 3D data are increasingly becoming publicly available. Yet, calculating structural metrics from LiDAR data can often be complex and time‐consuming and potentially requires expert knowledge. We present the R package Individual Tree Structural Metrics (ITSMe), a toolbox that works with LiDAR tree point clouds and quantitative structure models (QSMs) derived from LiDAR point clouds to obtain individual tree structural metrics. It serves as a robust synthesis framework for researchers who want to readily obtain structural information from 3D data of individual trees. The package includes functions to determine basic structural metrics (tree height, diameter at breast height, diameter above buttresses, projected crown area, 3D alpha crown volume) from individual tree point clouds, as well as more complex structural metrics (individual tree component volumes, branch angle‐, radius‐ and length‐related metrics) from QSMs. The ITSMe package is an open‐source package hosted on GitHub that will make the use of 3D data more straightforward and transparent for a range of end‐users interested in exploiting tree structure information. |
| first_indexed | 2024-03-12T20:33:14Z |
| format | Article |
| id | doaj.art-5f1dc501520c4d0d8d85168dd27bbf10 |
| institution | Directory Open Access Journal |
| issn | 2041-210X |
| language | English |
| last_indexed | 2024-03-12T20:33:14Z |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Methods in Ecology and Evolution |
| spelling | doaj.art-5f1dc501520c4d0d8d85168dd27bbf102023-08-01T18:55:41ZengWileyMethods in Ecology and Evolution2041-210X2023-01-0114123124110.1111/2041-210X.14026Analysing individual 3D tree structure using the R package ITSMeLouise Terryn0Kim Calders1Markku Åkerblom2Harm Bartholomeus3Mathias Disney4Shaun Levick5Niall Origo6Pasi Raumonen7Hans Verbeeck8CAVElab – Computational and Applied Vegetation Ecology, Department of Environment Ghent University Ghent BelgiumCAVElab – Computational and Applied Vegetation Ecology, Department of Environment Ghent University Ghent BelgiumComputing Sciences, Tampere University Tampere FinlandWageningen University & Research, Laboratory of Geo‐Information Science and Remote Sensing Wageningen The NetherlandsUCL Department of Geography London UKCSIRO Land and Water Winnellie Northwest Territories AustraliaClimate and Earth Observation group ‐ National Physical Laboratory Teddington UKComputing Sciences, Tampere University Tampere FinlandCAVElab – Computational and Applied Vegetation Ecology, Department of Environment Ghent University Ghent BelgiumAbstract Detailed 3D quantification of tree structure plays a crucial role in understanding tree‐ and plot‐level biophysical processes. Light detection and ranging (LiDAR) has led to a revolution in tree structural measurements and its 3D data are increasingly becoming publicly available. Yet, calculating structural metrics from LiDAR data can often be complex and time‐consuming and potentially requires expert knowledge. We present the R package Individual Tree Structural Metrics (ITSMe), a toolbox that works with LiDAR tree point clouds and quantitative structure models (QSMs) derived from LiDAR point clouds to obtain individual tree structural metrics. It serves as a robust synthesis framework for researchers who want to readily obtain structural information from 3D data of individual trees. The package includes functions to determine basic structural metrics (tree height, diameter at breast height, diameter above buttresses, projected crown area, 3D alpha crown volume) from individual tree point clouds, as well as more complex structural metrics (individual tree component volumes, branch angle‐, radius‐ and length‐related metrics) from QSMs. The ITSMe package is an open‐source package hosted on GitHub that will make the use of 3D data more straightforward and transparent for a range of end‐users interested in exploiting tree structure information.https://doi.org/10.1111/2041-210X.14026LiDARquantitative structure modelsR packagetree structural metrics |
| spellingShingle | Louise Terryn Kim Calders Markku Åkerblom Harm Bartholomeus Mathias Disney Shaun Levick Niall Origo Pasi Raumonen Hans Verbeeck Analysing individual 3D tree structure using the R package ITSMe Methods in Ecology and Evolution LiDAR quantitative structure models R package tree structural metrics |
| title | Analysing individual 3D tree structure using the R package ITSMe |
| title_full | Analysing individual 3D tree structure using the R package ITSMe |
| title_fullStr | Analysing individual 3D tree structure using the R package ITSMe |
| title_full_unstemmed | Analysing individual 3D tree structure using the R package ITSMe |
| title_short | Analysing individual 3D tree structure using the R package ITSMe |
| title_sort | analysing individual 3d tree structure using the r package itsme |
| topic | LiDAR quantitative structure models R package tree structural metrics |
| url | https://doi.org/10.1111/2041-210X.14026 |
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