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Quantifying 3D structure and occlusion in dense tropical and temperate forests using close-range LiDAR


Schneider, Fabian D; Kükenbrink, Daniel; Schaepman, Michael E; Schimel, David S; Morsdorf, Felix (2019). Quantifying 3D structure and occlusion in dense tropical and temperate forests using close-range LiDAR. Agricultural and Forest Meteorology, 268:249-257.

Abstract

Terrestrial laser scanning (TLS) has emerged as a reference for three-dimensional measurements of forest structure as well as forest reconstruction and modeling. Ground-based measurements can be complemented by new light-weight sensors on unmanned aerial vehicles (UAVs) or laser scans from canopy cranes or towers. However, it is still largely unknown how much of the forest canopy volume can be sampled and how occlusion is spatially distributed. We present an approach for highly detailed 3D structure measurements based on TLS on the ground and above canopy measurements from a canopy crane or UAV platform, and assess their spatial sampling in terms of occlusion. Comparing the application in a dense tropical and temperate forest, we demonstrate the ability to sample the complete canopy volume with <2% occlusion at very high spatial resolution when combining ground and above canopy measurements. This is necessary for a full canopy reconstruction. Ground-based TLS can provide sufficient coverage when no sampling of leaves and branches at top of canopy is required, whereas UAV or tower-based measurements show considerable occlusion in the mid- and understory. We therefore recommend to perform above canopy measurements under leaf off conditions, in sparse forests, or as an addition to ground measurements if a full representation of the whole canopy is required at very high spatial resolution. The latter can pave the way for studies on light availability, micrometeorology, sensor simulations and algorithm testing and development.

Abstract

Terrestrial laser scanning (TLS) has emerged as a reference for three-dimensional measurements of forest structure as well as forest reconstruction and modeling. Ground-based measurements can be complemented by new light-weight sensors on unmanned aerial vehicles (UAVs) or laser scans from canopy cranes or towers. However, it is still largely unknown how much of the forest canopy volume can be sampled and how occlusion is spatially distributed. We present an approach for highly detailed 3D structure measurements based on TLS on the ground and above canopy measurements from a canopy crane or UAV platform, and assess their spatial sampling in terms of occlusion. Comparing the application in a dense tropical and temperate forest, we demonstrate the ability to sample the complete canopy volume with <2% occlusion at very high spatial resolution when combining ground and above canopy measurements. This is necessary for a full canopy reconstruction. Ground-based TLS can provide sufficient coverage when no sampling of leaves and branches at top of canopy is required, whereas UAV or tower-based measurements show considerable occlusion in the mid- and understory. We therefore recommend to perform above canopy measurements under leaf off conditions, in sparse forests, or as an addition to ground measurements if a full representation of the whole canopy is required at very high spatial resolution. The latter can pave the way for studies on light availability, micrometeorology, sensor simulations and algorithm testing and development.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
08 Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Global and Planetary Change
Life Sciences > Forestry
Life Sciences > Agronomy and Crop Science
Physical Sciences > Atmospheric Science
Uncontrolled Keywords:Atmospheric Science, Agronomy and Crop Science, Global and Planetary Change, Forestry
Language:English
Date:1 April 2019
Deposited On:24 Feb 2022 15:24
Last Modified:27 Jun 2024 01:36
Publisher:Elsevier
ISSN:0168-1923
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.agrformet.2019.01.033
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