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Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners

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Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners. / Paynter, Ian; Saenz, Edward; Genest, Daniel; Peri, Francesco; Erb, Angela; Li, Zhan; Wiggin, Kara; Muir, Jasmine; Raumonen, Pasi; Schaaf, Erica Skye; Strahler, Alan; Schaaf, Crystal.

In: Remote Sensing in Ecology and Conservation, Vol. 2, No. 4, 2016, p. 174-189.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Paynter, I, Saenz, E, Genest, D, Peri, F, Erb, A, Li, Z, Wiggin, K, Muir, J, Raumonen, P, Schaaf, ES, Strahler, A & Schaaf, C 2016, 'Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners', Remote Sensing in Ecology and Conservation, vol. 2, no. 4, pp. 174-189. https://doi.org/10.1002/rse2.26

APA

Paynter, I., Saenz, E., Genest, D., Peri, F., Erb, A., Li, Z., ... Schaaf, C. (2016). Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners. Remote Sensing in Ecology and Conservation, 2(4), 174-189. https://doi.org/10.1002/rse2.26

Vancouver

Paynter I, Saenz E, Genest D, Peri F, Erb A, Li Z et al. Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners. Remote Sensing in Ecology and Conservation. 2016;2(4):174-189. https://doi.org/10.1002/rse2.26

Author

Paynter, Ian ; Saenz, Edward ; Genest, Daniel ; Peri, Francesco ; Erb, Angela ; Li, Zhan ; Wiggin, Kara ; Muir, Jasmine ; Raumonen, Pasi ; Schaaf, Erica Skye ; Strahler, Alan ; Schaaf, Crystal. / Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners. In: Remote Sensing in Ecology and Conservation. 2016 ; Vol. 2, No. 4. pp. 174-189.

Bibtex - Download

@article{efbf9dbc60254470baf138023cd53964,
title = "Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners",
abstract = "A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations.",
keywords = "Compact biomass lidar (CBL), ecosystem properties, lidar, quantitative structure models, terrestrial lidar scanners, validation",
author = "Ian Paynter and Edward Saenz and Daniel Genest and Francesco Peri and Angela Erb and Zhan Li and Kara Wiggin and Jasmine Muir and Pasi Raumonen and Schaaf, {Erica Skye} and Alan Strahler and Crystal Schaaf",
year = "2016",
doi = "10.1002/rse2.26",
language = "English",
volume = "2",
pages = "174--189",
journal = "Remote Sensing in Ecology and Conservation",
issn = "2056-3485",
publisher = "Wiley",
number = "4",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Observing ecosystems with lightweight, rapid-scanning terrestrial lidar scanners

AU - Paynter, Ian

AU - Saenz, Edward

AU - Genest, Daniel

AU - Peri, Francesco

AU - Erb, Angela

AU - Li, Zhan

AU - Wiggin, Kara

AU - Muir, Jasmine

AU - Raumonen, Pasi

AU - Schaaf, Erica Skye

AU - Strahler, Alan

AU - Schaaf, Crystal

PY - 2016

Y1 - 2016

N2 - A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations.

AB - A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations.

KW - Compact biomass lidar (CBL), ecosystem properties, lidar, quantitative structure models, terrestrial lidar scanners, validation

U2 - 10.1002/rse2.26

DO - 10.1002/rse2.26

M3 - Article

VL - 2

SP - 174

EP - 189

JO - Remote Sensing in Ecology and Conservation

JF - Remote Sensing in Ecology and Conservation

SN - 2056-3485

IS - 4

ER -