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Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR

Tutkimustuotosvertaisarvioitu

Standard

Non-destructive tree volume estimation through quantitative structure modelling : Comparing UAV laser scanning with terrestrial LIDAR. / Brede, Benjamin; Calders, Kim; Lau, Alvaro; Raumonen, Pasi; Bartholomeus, Harm M.; Herold, Martin; Kooistra, Lammert.

julkaisussa: Remote Sensing of Environment, Vuosikerta 233, 111355, 01.11.2019.

Tutkimustuotosvertaisarvioitu

Harvard

Brede, B, Calders, K, Lau, A, Raumonen, P, Bartholomeus, HM, Herold, M & Kooistra, L 2019, 'Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR', Remote Sensing of Environment, Vuosikerta. 233, 111355. https://doi.org/10.1016/j.rse.2019.111355

APA

Brede, B., Calders, K., Lau, A., Raumonen, P., Bartholomeus, H. M., Herold, M., & Kooistra, L. (2019). Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR. Remote Sensing of Environment, 233, [111355]. https://doi.org/10.1016/j.rse.2019.111355

Vancouver

Author

Brede, Benjamin ; Calders, Kim ; Lau, Alvaro ; Raumonen, Pasi ; Bartholomeus, Harm M. ; Herold, Martin ; Kooistra, Lammert. / Non-destructive tree volume estimation through quantitative structure modelling : Comparing UAV laser scanning with terrestrial LIDAR. Julkaisussa: Remote Sensing of Environment. 2019 ; Vuosikerta 233.

Bibtex - Lataa

@article{c3cddecae3904afbb65e474dc61057b1,
title = "Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR",
abstract = "Above-Ground Biomass (AGB) product calibration and validation require ground reference plots at hectometric scales to match space-borne missions' resolution. Traditional forest inventory methods that use allometric equations for single tree AGB estimation suffer from biases and low accuracy, especially when dealing with large trees. Terrestrial Laser Scanning (TLS) and explicit tree modelling show high potential for direct estimates of tree volume, but at the cost of time demanding fieldwork. This study aimed to assess if novel Unmanned Aerial Vehicle Laser Scanning (UAV-LS) could overcome this limitation, while delivering comparable results. For this purpose, the performance of UAV-LS in comparison with TLS for explicit tree modelling was tested in a Dutch temperate forest. In total, 200 trees with Diameter at Breast Height (DBH) ranging from 6 to 91 cm from 5 stands, including coniferous and deciduous species, have been scanned, segmented and subsequently modelled with TreeQSM. TreeQSM is a method that builds explicit tree models from laser scanner point clouds. Direct comparison with TLS derived models showed that UAV-LS reliably modelled the volume of trunks and branches with diameter ≥30 cm in the mature beech and oak stand with Concordance Correlation Coefficient (CCC) of 0.85 and RMSE of1.12 m3. Including smaller branch volume led to a considerable overestimation and decrease in correspondence to CCC of 0.51 and increase in RMSE to 6.59 m3. Denser stands prevented sensing of trunks and further decreased CCC to 0.36 in the Norway spruce stand. Also small, young trees posed problems by preventing a proper depiction of the trunk circumference and decreased CCC to 0.01. This dependence on stand indicated a strong impact of canopy structure on the UAV-LS volume modelling capacity. Improved flight paths, repeated acquisition flights or alternative modelling strategies could improve UAV-LS modelling performance under these conditions. This study contributes to the use of UAV-LS for fast tree volume and AGB estimation on scales relevant for satellite AGB product calibration and validation.",
keywords = "Above-Ground Biomass (AGB), Forest, Laser scanning, Quantitative Structure Model (QSM), UAV",
author = "Benjamin Brede and Kim Calders and Alvaro Lau and Pasi Raumonen and Bartholomeus, {Harm M.} and Martin Herold and Lammert Kooistra",
year = "2019",
month = "11",
day = "1",
doi = "10.1016/j.rse.2019.111355",
language = "English",
volume = "233",
journal = "Remote Sensing of Environment",
issn = "0034-4257",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Non-destructive tree volume estimation through quantitative structure modelling

T2 - Comparing UAV laser scanning with terrestrial LIDAR

AU - Brede, Benjamin

AU - Calders, Kim

AU - Lau, Alvaro

AU - Raumonen, Pasi

AU - Bartholomeus, Harm M.

AU - Herold, Martin

AU - Kooistra, Lammert

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Above-Ground Biomass (AGB) product calibration and validation require ground reference plots at hectometric scales to match space-borne missions' resolution. Traditional forest inventory methods that use allometric equations for single tree AGB estimation suffer from biases and low accuracy, especially when dealing with large trees. Terrestrial Laser Scanning (TLS) and explicit tree modelling show high potential for direct estimates of tree volume, but at the cost of time demanding fieldwork. This study aimed to assess if novel Unmanned Aerial Vehicle Laser Scanning (UAV-LS) could overcome this limitation, while delivering comparable results. For this purpose, the performance of UAV-LS in comparison with TLS for explicit tree modelling was tested in a Dutch temperate forest. In total, 200 trees with Diameter at Breast Height (DBH) ranging from 6 to 91 cm from 5 stands, including coniferous and deciduous species, have been scanned, segmented and subsequently modelled with TreeQSM. TreeQSM is a method that builds explicit tree models from laser scanner point clouds. Direct comparison with TLS derived models showed that UAV-LS reliably modelled the volume of trunks and branches with diameter ≥30 cm in the mature beech and oak stand with Concordance Correlation Coefficient (CCC) of 0.85 and RMSE of1.12 m3. Including smaller branch volume led to a considerable overestimation and decrease in correspondence to CCC of 0.51 and increase in RMSE to 6.59 m3. Denser stands prevented sensing of trunks and further decreased CCC to 0.36 in the Norway spruce stand. Also small, young trees posed problems by preventing a proper depiction of the trunk circumference and decreased CCC to 0.01. This dependence on stand indicated a strong impact of canopy structure on the UAV-LS volume modelling capacity. Improved flight paths, repeated acquisition flights or alternative modelling strategies could improve UAV-LS modelling performance under these conditions. This study contributes to the use of UAV-LS for fast tree volume and AGB estimation on scales relevant for satellite AGB product calibration and validation.

AB - Above-Ground Biomass (AGB) product calibration and validation require ground reference plots at hectometric scales to match space-borne missions' resolution. Traditional forest inventory methods that use allometric equations for single tree AGB estimation suffer from biases and low accuracy, especially when dealing with large trees. Terrestrial Laser Scanning (TLS) and explicit tree modelling show high potential for direct estimates of tree volume, but at the cost of time demanding fieldwork. This study aimed to assess if novel Unmanned Aerial Vehicle Laser Scanning (UAV-LS) could overcome this limitation, while delivering comparable results. For this purpose, the performance of UAV-LS in comparison with TLS for explicit tree modelling was tested in a Dutch temperate forest. In total, 200 trees with Diameter at Breast Height (DBH) ranging from 6 to 91 cm from 5 stands, including coniferous and deciduous species, have been scanned, segmented and subsequently modelled with TreeQSM. TreeQSM is a method that builds explicit tree models from laser scanner point clouds. Direct comparison with TLS derived models showed that UAV-LS reliably modelled the volume of trunks and branches with diameter ≥30 cm in the mature beech and oak stand with Concordance Correlation Coefficient (CCC) of 0.85 and RMSE of1.12 m3. Including smaller branch volume led to a considerable overestimation and decrease in correspondence to CCC of 0.51 and increase in RMSE to 6.59 m3. Denser stands prevented sensing of trunks and further decreased CCC to 0.36 in the Norway spruce stand. Also small, young trees posed problems by preventing a proper depiction of the trunk circumference and decreased CCC to 0.01. This dependence on stand indicated a strong impact of canopy structure on the UAV-LS volume modelling capacity. Improved flight paths, repeated acquisition flights or alternative modelling strategies could improve UAV-LS modelling performance under these conditions. This study contributes to the use of UAV-LS for fast tree volume and AGB estimation on scales relevant for satellite AGB product calibration and validation.

KW - Above-Ground Biomass (AGB)

KW - Forest

KW - Laser scanning

KW - Quantitative Structure Model (QSM)

KW - UAV

U2 - 10.1016/j.rse.2019.111355

DO - 10.1016/j.rse.2019.111355

M3 - Article

VL - 233

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

M1 - 111355

ER -