Terrain analyses and surface velocity measurements of the Hiorthfjellet rock glacier, Svalbard

2003 ◽  
Vol 14 (4) ◽  
pp. 359-365 ◽  
Author(s):  
Rune S. Ødegård ◽  
Ketil Isaksen ◽  
Trond Eiken ◽  
Johan Ludvig Sollid
Keyword(s):  
Surface Velocity ◽  
Velocity Measurements ◽  
Rock Glacier

Schmidt-hammer exposure-age dating (SHD) of rock glaciers in the Schöderkogel-Eisenhut area, Schladminger Tauern Range, Austria

The Holocene ◽  
2011 ◽  
Vol 22 (7) ◽  
pp. 761-771 ◽  
Author(s):  
Matthias Rode ◽  
Andreas Kellerer-Pirklbauer
Keyword(s):  
Root Zone ◽  
Age Dating ◽  
Surface Velocity ◽  
Schmidt Hammer ◽  
Rock Glacier ◽  
Relative Age ◽  
Exposure Age ◽  
Rock Glaciers ◽  
Glacier Length ◽  
Eastern Austria

Schmidt-hammer rebound values ( R-values) enable relative-age dating of landforms, with R-values relating to degree of weathering and therefore length of exposure. This method – recently termed as Schmidt-hammer exposure-age dating (SHD) – was applied to date five rock glaciers (size range, 0.01–0.12 km2) and one recent rockfall deposit at the study area Schöderkogel-Eisenhut, in the Schladminger Tauern Range (14°03′E, 47°15′N), Austria. The rock glaciers consist of gneiss or high metamorphic series of mica-schist that are comparable in their R-values. Four of them are relict (permafrost absent) and one is intact (containing patches of permafrost). On each of the five rock glaciers, SHD was carried out at 4–6 sites (50 measurements per site) along a longitudinal transect from the frontal ridge to the root zone. Results at all five rock glaciers are generally consistent with each other sharing statistically significant R-values along transects. The range between the highest and the lowest mean R-value at each of the five rock glaciers is 9.9–5.2. Using rock glacier length and surface velocity data from nearby sites, the rock glacier development must have lasted for several thousand years. Furthermore, by using SHD results from rock glaciers of known age from other sites in the region with comparable geology, approximate surface ages of 6.7–11.4 ka were estimated. This indicates long formation periods for all five rock glaciers. Our results suggest that many of the 1300 relict rock glaciers in central and eastern Austria were formed over a long period during the Lateglacial and Holocene period.

Position Registration of Scanning Lasers for Experimental Spatial Dynamics Modeling

1994 ◽  
Author(s):  
David E. Montgomery ◽  
Robert L. West
Keyword(s):  
Spatial Dynamics ◽  
Spatial Models ◽  
Laser Doppler Vibrometer ◽  
Sample Surface ◽  
Surface Shape ◽  
Surface Velocity ◽  
Multiple Point ◽  
Range Data ◽  
Dynamics Modeling ◽  
Velocity Measurements

Abstract Experimental spatial dynamics modeling involves using scanning lasers to sample surface shape and dynamic response of structures in order to verify structural dynamics design intent. Formation of accurate spatial models from laser-based measurements requires that laser position and orientation be registered relative to a fixed coordinate system. A three point direct registration procedure is defined for shape modeling using laser range and mirror deflection angles. Surface velocity measurements with a portable laser Doppler vibrometer (LDV) also require registration, but range information is unavailable. A multiple point indirect registration algorithm for the LDV is described that involves minimizing three nonlinear equations. A simulated laser rangefinder (LRF) was developed for demonstrating three point direct registration. The 3-D geometry of a compressor housing was modeled by combining range data from multiple laser positions. The multiple point indirect registration was applied to 3-D velocity response field reconstruction of a composite plate from velocity measurements scanned at three separate positions.

Reconstruction of the dynamics and origin of rock glaciers in an Alpine environment

2021 ◽  
Author(s):  
Benjamin Lehmann ◽  
Robert S. Anderson ◽  
Xavier Bodin ◽  
Pierre G. Valla ◽  
Julien Carcaillet
Keyword(s):  
Remote Sensing ◽  
Time Scales ◽  
Surface Velocity ◽  
Rock Glacier ◽  
Alpine Environment ◽  
Mountain Ranges ◽  
Long Time ◽  
Rock Glaciers ◽  
Alpine Environments ◽  
Alpine Valleys

<p>Rock glaciers are one of the most frequent cryospheric landform in mid-latitude mountain ranges. They influence the evolution of alpine environments on short (years to decades) and long (centuries to millennia) time scales. As a visible expression of mountain permafrost [1] as well as an important water reserve in the form of ground ice [2], rock glaciers are seen as increasingly important in the evolution of geomorphology and hydrology of mountain systems in the context of climate change and deglaciation [3, 4]. On longer time scales, rock glaciers transport boulders produced by the erosion of the headwall upstream and downstream and therefore participate in shaping mountain slopes [5]. Despite their importance, the dynamics and origin of rock glaciers are poorly understood.</p><p>In this study, we propose to address two questions:</p><p>1) How does the dynamics of rock glaciers change over time?</p><p>2) What is the origin of rock glaciers and what is their influence on the evolution of alpine environments?</p><p>These two questions require an evaluation of the surface velocity field of rock glaciers by relating short and long time scales. To solve this problem, we combine complementary methods including remote sensing, geochronology with a mechanical model of rock glacier dynamics. We apply this approach to the rock glacier complex of the Vallon de la Route in the Massif du Combeynot (French alps).</p><p>In order to reconstruct the displacement field of the rock glacier on modern time scales, we used remote sensing methods (i.e., image correlation and InSAR). Over longer periods (10<sup>3</sup> to 10<sup>4</sup> years), we used cosmogenic terrestrial nuclides (TCN) dating. By applying this methodology to boulder surfaces at different positions along the central flow line of the rock glacier, from the headwall to its terminus, we will be able to convert the exposure ages into surface displacement. The use of dynamic modelling of rock glaciers [6] will allow us to relate the surface kinematics to short to long time scales. It will then be possible to discuss the age, origin of rock glaciers and how topo-climatic and geomorphological processes control their evolution in Alpine environment.</p><p> </p><p>[1] Barsch, D.: Rockglaciers. Indicators for the Present and Former Geoecology in High Mountain Environments, Springer series in physical environment vol. 16, Springer, Berlin, Heidelberg, 1996.</p><p>[2] Jones, D. B., Harrison, S., Anderson, K., and Whalley, W. B.: Rock glaciers and mountain hydrology: A review, Earth-Sci Rev, 193, 66–90, 2019.</p><p>[3] Haeberli, W., Schaub, Y., and Huggel, C.: Increasing risks related to landslides from degrading permafrost into new lakes in deglaciating mountain ranges, Geomorphology, 293, 405–417, 2017.</p><p>[4] Knight, J., Harrison, S., and Jones, D. B.: Rock glaciers and the geomorphological evolution of deglacierizing mountains, Geomorphology, 324, 14–24, 2019.</p><p>[5] MacGregor, K.R., Anderson, R.S., Waddington, E.D.: Numerical modeling of glacial erosion and headwall processes in alpine valleys. Geomorphology 103 (2):189–204, 2009.</p><p>[6] Anderson, R. S., Anderson, L. S., Armstrong, W. H., Rossi, M. W., & Crump, S. E.: Glaciation of alpine valleys: The glacier–debris-covered glacier–rock glacier continuum. Geomorphology, 311, 127-142, 2018.</p>

scholarly journals Measurement of Surface Strain-Rate on Taku Glacier, Alaska

1964 ◽  
Vol 5 (39) ◽  
pp. 305-313 ◽  
Author(s):  
T. H. Wu ◽  
R. W. Christensen
Keyword(s):  
Strain Rate ◽  
Reasonable Agreement ◽  
Stress Condition ◽  
Surface Strain ◽  
Surface Velocity ◽  
Strain Rates ◽  
Velocity Measurements ◽  
Measured Velocity ◽  
Valley Glacier ◽  
Measured Strain

AbstractStrain-rate and surface velocity measurements were made on a valley glacier. The measured strain-rates were used to calculate the stress condition and velocity distribution in the glacier. The measured velocity is in reasonable agreement with that calculated from Nye’s plasticity solution.

Surface velocity and mass balance of Ice Streams D and E, West Antarctica

1996 ◽  
Vol 42 (142) ◽  
pp. 461-475 ◽  
Author(s):  
Robert Bindschadler ◽  
Patricia Vornberger ◽  
Donald Blankenship ◽  
Ted Scambos ◽  
Robert Jacobel
Keyword(s):  
Mass Balance ◽  
Surface Velocity ◽  
Random Errors ◽  
West Antarctica ◽  
Velocity Measurements ◽  
Ice Streams ◽  
Ice Stream ◽  
Data Density ◽  
Basal Shear ◽  
Collection Methods

AbstractOver 75 000 surface-velocity measurements are extracted from sequential satellite imagery of Ice Streams D and E to reveal a complex pattern of flow not apparent from previous measurements. Horizontal and vertical strain rates, calculated from surface velocity, indicate that the bed experiences larger basal shear where the surface of these ice streams is rougher. Ten airborne-radar profiles and one surface-based radar profile of ice thickness make possible the calculation of mass balance for longitudinal sections of each ice stream. Improved data-collection methods increase data density, substantially reducing random errors in velocity. However, systematic errors continue to limit the ability of the flux-differencing technique used here to resolve local variations in mass balance. Nevertheless, significant local variations in mass balance are revealed, while, overall, Ice Streams D and E are in approximate equilibrium. An earlier estimate of the net mass balance for Ice Stream D is improved.

Inventory of active rock glaciers in the western Nyainqêntanglha Range, Tibetan Plateau

2021 ◽  
Author(s):  
Eike Reinosch ◽  
Markus Gerke ◽  
Björn Riedel ◽  
Antje Schwalb ◽  
Qinghua Ye ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
High Reliability ◽  
Surface Velocity ◽  
Windward Side ◽  
Mountain Range ◽  
The Tibetan Plateau ◽  
Automated Classification ◽  
Rock Glacier ◽  
North West ◽  
Rock Glaciers

<p>The western Nyainqêntanglha Range on the Tibetan Plateau (TP) reaches an elevation of 7162 m and is characterized by an extensive periglacial environment. Here, we present the first rock glacier inventory of the central TP containing 1433 rock glaciers over an area of 4622 km². The rock glaciers are identified based on their surface velocity. The surface velocity is derived from Sentinel-1 satellite data of 2016 to 2019 via InSAR time series analysis. 16.4 % of the inventoried rock glaciers are classified as active with a surface velocity above 10 cmyr<sup>-1</sup> and 80.0 % are classified as transitional with 1 to 10 cmyr<sup>-1</sup>. The western Nyainqêntanglha Range forms a climate divide between the dry continental climate brought by the Westerlies from the north-west and the Indian Summer Monsoon to the south. 89.7 % of all active rock glaciers and 74 % of the free ice glacial area are located on the southern side. The higher moisture availability on the southern (windward) side of the mountain range is likely the cause of a higher rock glacier occurrence and the greater activity.</p><p>Manually identifying and outlining rock glaciers is time consuming and subjective. To ensure a high reliability and comparability of our inventory, we therefore combined a manual approach with an automated classification. Three analysts worked in tandem to generate the manual outlines according to the guidelines of the IPA action group on ‘Rock glacier inventories and kinematics’. A subset of these outlines acted as training areas for a pixel-based maximum likelihood classification. Both the manual and the automated classification were performed based on DEM parameters (elevation, slope etc.), optical datasets (Sentinel-2 and NDVI) and surface velocity (generated with InSAR). 87.8 % of all manually outlined rock glaciers were identified successfully at a true positive rate of 69.5 %. 18 additional rock glaciers were added to the inventory based on the automated classification. This combined approach is therefore beneficial to generate a complete inventory. The automated classification can, however, not replace the expertise of an analyst as it greatly overestimates the actual rock glacier area.</p>

Inversion of P-SV seismic data

Geophysics ◽  
1986 ◽  
Vol 51 (5) ◽  
pp. 1056-1068 ◽  
Author(s):  
James J. Carazzone
Keyword(s):  
Plane Wave ◽  
Riccati Equation ◽  
Incidence Angle ◽  
Surface Velocity ◽  
Complex Frequency ◽  
Velocity Measurements ◽  
Surface Source ◽  
Matrix Riccati Equation ◽  
Wave Incidence ◽  
Plane Wave Incidence

In a layered elastic material, density, shear velocity, and compressional velocity can be found at any depth from broadband surface measurements at two distinct, nonzero, precritical values of plane‐wave incidence angle. Layer‐stripping inversion uses three‐component surface velocity measurements generated by a polarized surface source to determine subsurface properties incrementally. The surface velocity measurements initialize a first‐order, nonlinear, matrix Riccati equation (derived from the elastic wave equation) which takes advantage of an attractive fixed‐point condition in the complex frequency plane to extract subsurface mechanical impedances. Subsurface density and velocities are recovered from the inverted impedances at two or more plane‐wave incidence angles. General properties of the matrix Riccati equation in the complex frequency plane aid in incorporating bandwidth constraints. Inversion of synthetic plane wave data from a piece‐wise continuous model illustrates inversion effects when only a finite bandwidth is available and when different compressional and shear wavelength distance scales are present.

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