Relationship between Mean Free Path and Leaf Area in Boreal Forest Canopies
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概要
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The free (unobstructed) sight through the foliage layer of forest canopy is expected to depend on the density of the foliage, i.e. dense foliage shortens the free sight while sparse one extends it. Conversely, it is possible to estimate foliage density from the free sight. Furthermore, it is possible to estimate from the free sight the amount of leaves in terms of leaf area or leaf area index (LAI) as a product of estimated foliage density and the thickness of the foliage layer. This paper presents a simple theory of estimating LAI from the free sight along with its verification using a set of field data from boreal forest of Canada. Free sight through the canopy was measured using airborne laser altimetry (ALA). Laser beams emitted vertically from an aircraft are reflected from different layers of the canopy, ranging from the uppermost canopy surface to the ground. The distance that a laser beam travels unimpeded into the canopy was assumed to be the free sight or more aptly, the free path, and the mean of a number of penetrations within the canopy as a good measure of the amount of leaf area. We assembled a set of field leaf area and mean free path data for 13 boreal forest sites in central Alberta, Canada. We related leaf area density with mean free path and found an inverse relationship between them. Furthermore, we verified that LAI can be estimated as a product of mean free path-based leaf area density and an estimate of canopy depth (D) obtained based on the relationships we found between D and mean tree height (H) and between H and mean laser vegetation height.
- 森林計画学会の論文
著者
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Abraham Emmanuel
Makiling Center For Mountain Ecosystems College Of Forestry And Natural Resources University Of The
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Tsuzuki Hayato
The United Graduate School Of Agricultural Sciences Ehime University
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Sweda Tatsuo
The United Graduate School of Agricultural Sciences, Ehime University
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Sweda Tatsuo
The United Graduate School Of Agricultural Sciences Ehime University