Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning

<p>Understanding the impact of tree structure on snow depth and extent is important in order to make predictions of snow amounts and how changes in forest cover may affect future water resources. In this work, we investigate snow depth under tree canopies and in open areas to quantify the role...

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Main Authors: A. Hojatimalekshah, Z. Uhlmann, N. F. Glenn, C. A. Hiemstra, C. J. Tennant, J. D. Graham, L. Spaete, A. Gelvin, H.-P. Marshall, J. P. McNamara, J. Enterkine
Format: Article
Language:English
Published: Copernicus Publications 2021-05-01
Series:The Cryosphere
Online Access:https://tc.copernicus.org/articles/15/2187/2021/tc-15-2187-2021.pdf
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spelling doaj-209873fdae51425ea27ded376e6c93e52021-05-06T06:20:07ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242021-05-01152187220910.5194/tc-15-2187-2021Tree canopy and snow depth relationships at fine scales with terrestrial laser scanningA. Hojatimalekshah0Z. Uhlmann1N. F. Glenn2C. A. Hiemstra3C. J. Tennant4J. D. Graham5L. Spaete6A. Gelvin7H.-P. Marshall8J. P. McNamara9J. Enterkine10Department of Geosciences, Boise State University, Boise, ID 83725, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USAUS Department of Agriculture, Forest Service, Geospatial Management Office, Salt Lake City, UT 84138, USAUS Army Corps of Engineers, Sacramento, CA 95814, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USAMinnesota Department of Natural Resources, Division of Forestry, Resource Assessment, Grand Rapids, MN 55744, USAUS Army Corps of Engineer, Cold Regions Research and Engineering Laboratory, Hanover, NH 03755, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USADepartment of Geosciences, Boise State University, Boise, ID 83725, USA<p>Understanding the impact of tree structure on snow depth and extent is important in order to make predictions of snow amounts and how changes in forest cover may affect future water resources. In this work, we investigate snow depth under tree canopies and in open areas to quantify the role of tree structure in controlling snow depth, as well as the controls from wind and topography. We use fine-scale terrestrial laser scanning (TLS) data collected across Grand Mesa, Colorado, USA (winter 2016–2017), to measure the snow depth and extract horizontal and vertical tree descriptors (metrics) at six sites. We utilize these descriptors along with topographical metrics in multiple linear and decision tree regressions to investigate snow depth variations under the canopy and in open areas. Canopy, topography, and snow interaction results indicate that vegetation structural metrics (specifically foliage height diversity; FHD) along with local-scale processes like wind and topography are highly influential in snow depth variation. Our study specifies that windward slopes show greater impact on snow accumulation than vegetation metrics. In addition, the results indicate that FHD can explain up to 27 % of sub-canopy snow depth variation at sites where the effect of topography and wind is negligible. Solar radiation and elevation are the dominant controls on snow depth in open areas. Fine-scale analysis from TLS provides information on local-scale controls and provides an opportunity to be readily coupled with lidar or photogrammetry from uncrewed aerial systems (UASs) as well as airborne and spaceborne platforms to investigate larger-scale controls on snow depth.</p>https://tc.copernicus.org/articles/15/2187/2021/tc-15-2187-2021.pdf
collection DOAJ
language English
format Article
sources DOAJ
author A. Hojatimalekshah
Z. Uhlmann
N. F. Glenn
C. A. Hiemstra
C. J. Tennant
J. D. Graham
L. Spaete
A. Gelvin
H.-P. Marshall
J. P. McNamara
J. Enterkine
spellingShingle A. Hojatimalekshah
Z. Uhlmann
N. F. Glenn
C. A. Hiemstra
C. J. Tennant
J. D. Graham
L. Spaete
A. Gelvin
H.-P. Marshall
J. P. McNamara
J. Enterkine
Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
The Cryosphere
author_facet A. Hojatimalekshah
Z. Uhlmann
N. F. Glenn
C. A. Hiemstra
C. J. Tennant
J. D. Graham
L. Spaete
A. Gelvin
H.-P. Marshall
J. P. McNamara
J. Enterkine
author_sort A. Hojatimalekshah
title Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
title_short Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
title_full Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
title_fullStr Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
title_full_unstemmed Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
title_sort tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
publisher Copernicus Publications
series The Cryosphere
issn 1994-0416
1994-0424
publishDate 2021-05-01
description <p>Understanding the impact of tree structure on snow depth and extent is important in order to make predictions of snow amounts and how changes in forest cover may affect future water resources. In this work, we investigate snow depth under tree canopies and in open areas to quantify the role of tree structure in controlling snow depth, as well as the controls from wind and topography. We use fine-scale terrestrial laser scanning (TLS) data collected across Grand Mesa, Colorado, USA (winter 2016–2017), to measure the snow depth and extract horizontal and vertical tree descriptors (metrics) at six sites. We utilize these descriptors along with topographical metrics in multiple linear and decision tree regressions to investigate snow depth variations under the canopy and in open areas. Canopy, topography, and snow interaction results indicate that vegetation structural metrics (specifically foliage height diversity; FHD) along with local-scale processes like wind and topography are highly influential in snow depth variation. Our study specifies that windward slopes show greater impact on snow accumulation than vegetation metrics. In addition, the results indicate that FHD can explain up to 27 % of sub-canopy snow depth variation at sites where the effect of topography and wind is negligible. Solar radiation and elevation are the dominant controls on snow depth in open areas. Fine-scale analysis from TLS provides information on local-scale controls and provides an opportunity to be readily coupled with lidar or photogrammetry from uncrewed aerial systems (UASs) as well as airborne and spaceborne platforms to investigate larger-scale controls on snow depth.</p>
url https://tc.copernicus.org/articles/15/2187/2021/tc-15-2187-2021.pdf
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