Review of Hojatimalekshah et al., “Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning“

Abstract. 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, to measure the snow depth and extract horizontal and vertical tree descriptors (metrics) at six sites. We apply the Marker-controlled watershed algorithm for individual tree segmentation and measure the snow depth using the Multi-scale Model to Model Cloud Comparison algorithm. Canopy, topography and snow interaction results indicate that vegetation structural metrics (specifically foliage height diversity) along with local scale processes such as wind are highly influential on snow depth variation. Our study specifies that windward slopes show greater impact on snow accumulation than vegetation metrics. In addition, the results emphasize the importance of tree species and distribution on snow depth patterns. Fine scale analysis from TLS provides information on local scale controls, and provides an opportunity to be readily coupled with airborne or spaceborne lidar to investigate larger-scale controls on snow depth.

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Combining UAV LiDAR and Terrestrial Laser Scanning to investigate the impact of shrub expansion on local-scale Arctic snowpack distribution.

10.5194/egusphere-egu2020-17714 ◽

2020 ◽

Author(s):

Maxim Lamare ◽

Laurent Arnaud ◽

Ghislain Picard ◽

Maude Pelletier ◽

Florent Domine

Keyword(s):

Snow Depth ◽

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Snow Accumulation ◽

Surface Model ◽

Shrub Expansion ◽

Vegetation Height ◽

Digital Terrain ◽

Dwarf Birch ◽

The Impact

Climate warming induces shrub expansion on Arctic herb tundra, with effects on snow trapping and hence snow depth. We have used UAV-borne LiDAR and Terrestrial Laser Scanning (TLS) to investigate the impact of shrub height on snow depth at two close sites near Umiujaq, eastern Canadian low Arctic, where dwarf birch and willow shrubs are expanding on lichen tundra. The first site features lichen and high shrubs (50-100 cm), a moderate relief, and a snowpack averaging 95 cm in spring. The second site consists of lichen and low shrubs (20-60 cm), more pronounced topography, and a deeper snowpack (101 cm). Digital Terrain and Surface Models were acquired in early fall to obtain topography and vegetation height. A Digital Surface Model obtained in spring produced snow depth maps at peak depth. TLS over a 400 m2 area produced time series of snow depth throughout the winter. TLS data show preferential snow accumulation in shrubs, but also preferential melting in shrubs during fall warm spells and in spring. UAV data at the first site show a strong correlation between vegetation height and snow depth, even after snow depth has exceeded vegetation height. This correlation is not observed at the second site, probably because snow depth there is much greater than vegetation height. These data show the need to reconsider some paradigms on snow-vegetation interactions, for example that vegetation does not affect snow accumulation beyond its height.

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3D phenotyping of peach tree canopy architecture using terrestrial laser scanning

10.1002/essoar.10508842.1 ◽

2021 ◽

Author(s):

Jordan Knapp-Wilson ◽

Rafael Bohn Reckziegel ◽

Alexander Bucksch ◽

Dario J Chavez

Keyword(s):

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Tree Canopy ◽

Peach Tree ◽

Canopy Architecture

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A comparison of measurement methods: terrestrial laser scanning, tachymetry and snow probing for the determination of the spatial snow-depth distribution on slopes

Annals of Glaciology ◽

10.3189/172756408787814726 ◽

2008 ◽

Vol 49 ◽

pp. 210-216 ◽

Cited By ~ 106

Author(s):

A. Prokop ◽

M. Schirmer ◽

M. Rub ◽

M. Lehning ◽

M. Stocker

Keyword(s):

Snow Depth ◽

Laser Scanning ◽

Near Infrared ◽

Depth Distribution ◽

Terrestrial Laser Scanning ◽

Weather Conditions ◽

Measurement Methods ◽

Measuring System ◽

Protection Measures

AbstractDetermination of the spatial snow-depth distribution is important in potential avalanche-starting zones, both for avalanche prediction and for the dimensioning of permanent protection measures. Knowledge of the spatial distribution of snow is needed in order to validate snow depths computed from snowpack and snowdrift models. The inaccessibility of alpine terrain and the acute danger of avalanches complicate snow-depth measurements (e.g. when probes are used), so the possibility of measuring the snowpack using terrestrial laser scanning (TLS) was tested. The results obtained were compared to those of tachymetry and manual snow probing. Laser measurements were taken using the long-range laser profile measuring system Riegl LPM-i800HA. The wavelength used by the laser was 0.9 μm (near-infrared). The accuracy was typically within 30 mm. The highest point resolution was 30 mm when measured from a distance of 100 m. Tachymetry measurements were carried out using Leica TCRP1201 systems. Snowpack depths measured by the tachymeter were also used. The datasets captured by tachymetry were used as reference models to compare the three different methods (TLS, tachymetry and snow probing). This is the first time that the accuracy of TLS systems in snowy and alpine weather conditions has been quantified. The relative accuracy between the three measurement methods is bounded by a maximum offset of ±8 cm. Between TLS and the tachymeter the standard deviation is 1σ = 2 cm, and between manual probing and TLS it is up to 1σ = 10 cm, for maximum distances for the TLS and tachymeter of 300 m.

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Retrieval of three-dimensional tree canopy and shade using terrestrial laser scanning (TLS) data to analyze the cooling effect of vegetation

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2015.11.005 ◽

2016 ◽

Vol 217 ◽

pp. 22-34 ◽

Cited By ~ 41

Author(s):

Fanhua Kong ◽

Weijiao Yan ◽

Guang Zheng ◽

Haiwei Yin ◽

Gina Cavan ◽

...

Keyword(s):

Laser Scanning ◽

Three Dimensional ◽

Terrestrial Laser Scanning ◽

Tree Canopy ◽

Cooling Effect

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MAPPING SNOW DEPTH WITH AUTOMATED TERRESTRIAL LASER SCANNING – INVESTIGATING POTENTIAL APPLICATIONS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w4-537-2017 ◽

2017 ◽

Vol XLII-4/W4 ◽

pp. 537-540

Author(s):

M. S. Adams ◽

T. Gigele ◽

R. Fromm

Keyword(s):

Spatial Resolution ◽

Glass Fibre ◽

Snow Depth ◽

Laser Scanning ◽

Depth Distribution ◽

Explanatory Power ◽

Terrestrial Laser Scanning ◽

Snow Drift ◽

Potential Applications ◽

Research Questions

This contribution presents an automated terrestrial laser scanning (ATLS) setup, which was used during the winter 2016/17 to monitor the snow depth distribution on a NW-facing slope at a high-alpine study site. We collected data at high temporal [(sub-)daily] and spatial resolution (decimetre-range) over 0.8 km² with a Riegl LPM-321, set in a weather-proof glass fibre enclosure. Two potential ATLS-applications are investigated here: monitoring medium-sized snow avalanche events, and tracking snow depth change caused by snow drift. The results show the ATLS data’s high explanatory power and versatility for different snow research questions.

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