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On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements
The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning te...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829182/ https://www.ncbi.nlm.nih.gov/pubmed/29503720 http://dx.doi.org/10.1098/rsfs.2017.0039 |
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author | Li, Zhan Schaefer, Michael Strahler, Alan Schaaf, Crystal Jupp, David |
author_facet | Li, Zhan Schaefer, Michael Strahler, Alan Schaaf, Crystal Jupp, David |
author_sort | Li, Zhan |
collection | PubMed |
description | The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales. |
format | Online Article Text |
id | pubmed-5829182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-58291822018-03-02 On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements Li, Zhan Schaefer, Michael Strahler, Alan Schaaf, Crystal Jupp, David Interface Focus Articles The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales. The Royal Society 2018-04-06 2018-02-16 /pmc/articles/PMC5829182/ /pubmed/29503720 http://dx.doi.org/10.1098/rsfs.2017.0039 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Li, Zhan Schaefer, Michael Strahler, Alan Schaaf, Crystal Jupp, David On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title | On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title_full | On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title_fullStr | On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title_full_unstemmed | On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title_short | On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
title_sort | on the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829182/ https://www.ncbi.nlm.nih.gov/pubmed/29503720 http://dx.doi.org/10.1098/rsfs.2017.0039 |
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