Snow forces on forest plants due to creep and glide

Höller, Peter; Fromm, Reinhard; Leitinger, Georg

doi:10.1016/j.foreco.2008.09.035

Cited by 26 publications

(23 citation statements)

References 15 publications

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“…This implies that only glide rates with a high (2) or very high (1) intensity can be considered as critical for juvenescent trees. The necessary force to uproot young trees (stem diameter 0.025 m, height 0.5 m) is about 1,000 N (Höller et al 2009); according to Höller et al (2009), values of this magnitude can be regularly caused by gliding on a smooth ground surface (where glide rates correspond to a high (2) and very high (1) intensity). To ensure tree growth under these conditions, it may not be sufficient to plant a high number of tress.…”

Section: Discussionmentioning

confidence: 99%

“…To ensure tree growth under these conditions, it may not be sufficient to plant a high number of tress. Although 3,000 to 5,000 plants/ha were afforested in the surroundings of the experimental site (unpublished map of the Austrian Service for Torrent and Avalanche Control), many trees were damaged by intensive gliding (Höller et al 2009). In order to reduce gliding (and to avoid snow glide damages), appropriate measures (see below) must be considered.…”

Section: Discussionmentioning

confidence: 99%

“…However, juvenescent trees may also be uprooted from the ground, with several authors describing this type of damage to juvenescent trees (Höller et al 2009). According to In der Gand (1968b), plants can be uprooted as a result of snow gliding and the accompanying tensile forces.…”

Section: Introductionmentioning

confidence: 99%

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Snow gliding on a south-facing slope covered with larch trees

Höller

2013

Annals of Forest Science

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Snow gliding on a south-facing slope covered with larch trees

Höller

2013

Annals of Forest Science

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“…Surface roughness is relevant for glide avalanches on micro-level as well as for snow slabs on meso-and macro-level. The estimated skid factors are introduced in snow gliding and snow pressure modeling [9].…”

Section: Introductionmentioning

confidence: 99%

Roughness Mapping on Various Vertical Scales Based on Full-Waveform Airborne Laser Scanning Data

et al. 2011

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Abstract:Roughness is an important input parameter for modeling of natural hazards such as floods, rock falls and avalanches, where it is basically assumed that flow velocities decrease with increasing roughness. Seeing roughness as a multi-scale level concept (i.e., ranging from fine-scale soil characteristics to description of understory and lower tree layer) various roughness raster products were derived from the original full-waveform airborne laser scanning (FWF-ALS) point cloud using two different types of roughness parameters, the surface roughness (SR) and the terrain roughness (TR). For the calculation of the SR, ALS terrain points within a defined height range to the terrain surface are considered. For the parameterization of the SR, two approaches are investigated. In the first approach, a geometric description by calculating the standard deviation of plane fitting residuals of terrain points is used. In the second one, the potential of the derived echo widths are analyzed for the parameterization of SR. The echo width is an indicator for roughness and the slope of the target. To achieve a comparable spatial resolution of both SR layers, the calculation of the standard deviation of detrended terrain points requires a higher terrain point density than the SR parameterization using the echo widths. The TR describes objects (i.e., point clusters) close but explicitly above the terrain surface, with 20 cm defined as threshold height value for delineation of the surface layer (i.e., forest OPEN ACCESSRemote Sens. 2011, 3 504 floor layer). Two different empirically defined vegetation layers below the canopy layer were analyzed (TR I: 0.2 m to 1.0 m; TR II: 0.2 m to 3.0 m). A 1 m output grid cell size was chosen for all roughness parameters in order to provide consistency for further integration of high-resolution optical imagery. The derived roughness parameters were then jointly classified, together with a normalized Digital Surface Model (nDSM) showing the height of objects (i.e., trees) above ground. The presented approach enables the classification of forested areas in patches of different vegetation structure (e.g., varying soil roughness, understory, density of natural cover). For validation purposes in situ reference data were collected and cross-checked with the classification results, positively confirming the general feasibility of the proposed vertical concept of integrated roughness mapping on various vertical levels. Results can provide valuable input for forest mapping and monitoring, in particular with regard to natural hazard modeling.

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“…The slope angle, the micro relief, and the hydrological properties of the slope influence the glide velocity (Ceaglio et al, 2017;McClung and Schaerer, 1999;Margreth, 2007). Friction originated by the vegetation depends on its composition and height (Höller et al, 2009). Both the vegetation and the micro relief depend on the land use, which is an input for snow glide modeling (Leitinger et al, 2008;Maggioni et al, 2016).…”

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Determining the drivers for snow gliding

Fromm¹,

Baumgärtner²,

Leitinger³

et al. 2018

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Abstract. Snow gliding is a key factor for snow glide avalanche formation and soil erosion. This study considers atmospheric 10 and snow variables, vegetation characteristics, and soil properties, and determines their relevance for snow gliding at a test site (Wildkogel, Upper Pinzgau, Austria) during winter 2014/15. The time-dependent data were collected at a high temporal resolution. In addition to conventional sensors a 'snow melt analyzer' was used.

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Snow forces on forest plants due to creep and glide

Cited by 26 publications

References 15 publications

Snow gliding on a south-facing slope covered with larch trees

Snow gliding on a south-facing slope covered with larch trees

Roughness Mapping on Various Vertical Scales Based on Full-Waveform Airborne Laser Scanning Data

Determining the drivers for snow gliding

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