Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements

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Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements. / Liang, Xinlian; Wang, Yunsheng; Pyörälä, Jiri; Lehtomäki, Matti; Yu, Xiaowei; Kaartinen, Harri; Kukko, Antero; Honkavaara, Eija; Issaoui, Aimad E. I.; Nevalainen, Olli; Vaaja, Matti; Virtanen, Juho-Pekka; Katoh, Masato; Deng, Songqiu.

In: Forest ecosystems, Vol. 6, No. 1, 20, 01.12.2019.

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Harvard

Liang, X, Wang, Y, Pyörälä, J, Lehtomäki, M, Yu, X, Kaartinen, H, Kukko, A, Honkavaara, E, Issaoui, AEI, Nevalainen, O, Vaaja, M, Virtanen, J-P, Katoh, M & Deng, S 2019, 'Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements', Forest ecosystems, vol. 6, no. 1, 20. https://doi.org/10.1186/s40663-019-0173-3

APA

Liang, X., Wang, Y., Pyörälä, J., Lehtomäki, M., Yu, X., Kaartinen, H., ... Deng, S. (2019). Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements. Forest ecosystems, 6(1), [20]. https://doi.org/10.1186/s40663-019-0173-3

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Liang, Xinlian ; Wang, Yunsheng ; Pyörälä, Jiri ; Lehtomäki, Matti ; Yu, Xiaowei ; Kaartinen, Harri ; Kukko, Antero ; Honkavaara, Eija ; Issaoui, Aimad E. I. ; Nevalainen, Olli ; Vaaja, Matti ; Virtanen, Juho-Pekka ; Katoh, Masato ; Deng, Songqiu. / Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements. In: Forest ecosystems. 2019 ; Vol. 6, No. 1.

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@article{462977498f1640ed99f7a63d1282b7bc,
title = "Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements",
abstract = "Background: Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117-5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) - borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys.Results: The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions.Conclusions: This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations.",
keywords = "In situ, Point cloud, Terrestrial, Mobile, Above canopy, Unmanned aerial vehicle, Forest inventory, MAPPING SYSTEM, UAV-LIDAR, BIOMASS, HEIGHT",
author = "Xinlian Liang and Yunsheng Wang and Jiri Py{\"o}r{\"a}l{\"a} and Matti Lehtom{\"a}ki and Xiaowei Yu and Harri Kaartinen and Antero Kukko and Eija Honkavaara and Issaoui, {Aimad E. I.} and Olli Nevalainen and Matti Vaaja and Juho-Pekka Virtanen and Masato Katoh and Songqiu Deng",
year = "2019",
month = "12",
day = "1",
doi = "10.1186/s40663-019-0173-3",
language = "English",
volume = "6",
journal = "Forest ecosystems",
issn = "2095-6355",
number = "1",

}

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TY - JOUR

T1 - Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements

AU - Liang, Xinlian

AU - Wang, Yunsheng

AU - Pyörälä, Jiri

AU - Lehtomäki, Matti

AU - Yu, Xiaowei

AU - Kaartinen, Harri

AU - Kukko, Antero

AU - Honkavaara, Eija

AU - Issaoui, Aimad E. I.

AU - Nevalainen, Olli

AU - Vaaja, Matti

AU - Virtanen, Juho-Pekka

AU - Katoh, Masato

AU - Deng, Songqiu

PY - 2019/12/1

Y1 - 2019/12/1

N2 - Background: Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117-5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) - borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys.Results: The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions.Conclusions: This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations.

AB - Background: Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117-5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) - borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys.Results: The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions.Conclusions: This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations.

KW - In situ

KW - Point cloud

KW - Terrestrial

KW - Mobile

KW - Above canopy

KW - Unmanned aerial vehicle

KW - Forest inventory

KW - MAPPING SYSTEM

KW - UAV-LIDAR

KW - BIOMASS

KW - HEIGHT

UR - http://www.scopus.com/inward/record.url?scp=85066314710&partnerID=8YFLogxK

U2 - 10.1186/s40663-019-0173-3

DO - 10.1186/s40663-019-0173-3

M3 - Article

VL - 6

JO - Forest ecosystems

JF - Forest ecosystems

SN - 2095-6355

IS - 1

M1 - 20

ER -

ID: 33496814