Articles | Volume 15, issue 1
https://doi.org/10.5194/tc-15-69-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-69-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, 8092,
Switzerland
Pascal Sirguey
National School of Surveying, University of Otago, P.O. Box 56, Dunedin,
New Zealand
Aubrey Miller
National School of Surveying, University of Otago, P.O. Box 56, Dunedin,
New Zealand
Mauro Marty
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Birmensdorf, 8903, Switzerland
Konrad Schindler
Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, 8092,
Switzerland
Andreas Stoffel
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
Yves Bühler
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260,
Switzerland
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Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from piloted airplane to large (> 100 km2), very detailed and accurate snow depth maps around Davos (CH). In addition, we use these maps to describe the existed snow depth distribution and other special features.
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C. Stucker, B. Ke, Y. Yue, S. Huang, I. Armeni, and K. Schindler
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Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-112, https://doi.org/10.5194/nhess-2022-112, 2022
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This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large scale avalanche modeling method with a state of the art probilistic risk tool. Over 40'000 individual avalanches were simulated and a building dataset with over 13'000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
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Preprint under review for TC
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Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
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Y. Xie, K. Schindler, J. Tian, and X. X. Zhu
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Elisabeth D. Hafner, Frank Techel, Silvan Leinss, and Yves Bühler
The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, https://doi.org/10.5194/tc-15-983-2021, 2021
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Satellites prove to be very valuable for documentation of large-scale avalanche periods. To test reliability and completeness, which has not been satisfactorily verified before, we attempt a full validation of avalanches mapped from two optical sensors and one radar sensor. Our results demonstrate the reliability of high-spatial-resolution optical data for avalanche mapping, the suitability of radar for mapping of larger avalanches and the unsuitability of medium-spatial-resolution optical data.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Angus J. Dowson, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 14, 3425–3448, https://doi.org/10.5194/tc-14-3425-2020, https://doi.org/10.5194/tc-14-3425-2020, 2020
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Satellite observations over 19 years are used to characterise the spatial and temporal variability of surface albedo across the gardens of Eden and Allah, two of New Zealand’s largest ice fields. The variability in response of individual glaciers reveals the role of topographic setting and suggests that glaciers in the Southern Alps do not behave as a single climatic unit. There is evidence that the timing of the minimum surface albedo has shifted to later in the summer on 10 of the 12 glaciers.
Silvan Leinss, Raphael Wicki, Sämi Holenstein, Simone Baffelli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 20, 1783–1803, https://doi.org/10.5194/nhess-20-1783-2020, https://doi.org/10.5194/nhess-20-1783-2020, 2020
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To assess snow avalanche mapping with radar satellites in Switzerland, we compare 2 m resolution TerraSAR-X images, 10 m resolution Sentinel-1 images, and optical 1.5 m resolution SPOT-6 images. We found that radar satellites provide a valuable option to map at least larger avalanches, though avalanches are mapped only partially. By combining multiple orbits and polarizations from S1, we achieved mapping results of quality almost comparable to single high-resolution TerraSAR-X images.
Benjamin Walter, Hendrik Huwald, Josué Gehring, Yves Bühler, and Michael Lehning
The Cryosphere, 14, 1779–1794, https://doi.org/10.5194/tc-14-1779-2020, https://doi.org/10.5194/tc-14-1779-2020, 2020
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We applied a horizontally mounted low-cost precipitation radar to measure velocities, frequency of occurrence, travel distances and turbulence characteristics of blowing snow off a mountain ridge. Our analysis provides a first insight into the potential of radar measurements for determining blowing snow characteristics, improves our understanding of mountain ridge blowing snow events and serves as a valuable data basis for validating coupled numerical weather and snowpack simulations.
Jürg Schweizer, Christoph Mitterer, Frank Techel, Andreas Stoffel, and Benjamin Reuter
The Cryosphere, 14, 737–750, https://doi.org/10.5194/tc-14-737-2020, https://doi.org/10.5194/tc-14-737-2020, 2020
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Snow avalanches represent a major natural hazard in seasonally snow-covered mountain regions around the world. To avoid periods and locations of high hazard, avalanche warnings are issued by public authorities. In these bulletins, the hazard is characterized by a danger level. Since the danger levels are not well defined, we analyzed a large data set of avalanches to improve the description. Our findings show discrepancies in present usage of the danger scale and show ways to improve the scale.
Yves Bühler, Elisabeth D. Hafner, Benjamin Zweifel, Mathias Zesiger, and Holger Heisig
The Cryosphere, 13, 3225–3238, https://doi.org/10.5194/tc-13-3225-2019, https://doi.org/10.5194/tc-13-3225-2019, 2019
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We manually map 18 737 avalanche outlines based on SPOT6 optical satellite imagery acquired in January 2018. This is the most complete and accurate avalanche documentation of a large avalanche period covering a big part of the Swiss Alps. This unique dataset can be applied for the validation of other remote-sensing-based avalanche-mapping procedures and for updating avalanche databases to improve hazard maps.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
Hydrol. Earth Syst. Sci., 23, 3189–3217, https://doi.org/10.5194/hess-23-3189-2019, https://doi.org/10.5194/hess-23-3189-2019, 2019
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Spatio-temporal variability of seasonal snow cover is characterised from 16 years of MODIS data for the Clutha Catchment, New Zealand. No trend was detected in snow-covered area. Spatial modes of variability reveal the role of anomalous winter airflow. The sensitivity of snow cover duration to temperature and precipitation variability is found to vary spatially across the catchment. These findings provide new insight into seasonal snow processes in New Zealand and guidance for modelling efforts.
Andrin Caviezel, Sophia E. Demmel, Adrian Ringenbach, Yves Bühler, Guang Lu, Marc Christen, Claire E. Dinneen, Lucie A. Eberhard, Daniel von Rickenbach, and Perry Bartelt
Earth Surf. Dynam., 7, 199–210, https://doi.org/10.5194/esurf-7-199-2019, https://doi.org/10.5194/esurf-7-199-2019, 2019
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In rockfall hazard assessment, knowledge about the precise flight path of assumed boulders is vital for its accuracy. We present the full reconstruction of artificially induced rockfall events. The extracted information such as exact velocities, jump heights and lengths provide detailed insights into how rotating rocks interact with the ground. The information serves as future calibration of rockfall modelling tools with the goal of even more realistic modelling predictions.
Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, and Marc Christen
Nat. Hazards Earth Syst. Sci., 18, 3235–3251, https://doi.org/10.5194/nhess-18-3235-2018, https://doi.org/10.5194/nhess-18-3235-2018, 2018
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Coping with avalanche hazard has a long tradition in alpine countries. Hazard mapping has proven to be one of the most effective methods. In this paper we develop a new approach to automatically delineate avalanche release areas and connect them to state-of-the-art numerical avalanche simulations. This enables computer-based hazard indication mapping over large areas such as entire countries. This is of particular interest where hazard maps do not yet exist, such as in developing countries.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, https://doi.org/10.5194/tc-12-3477-2018, 2018
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A remotely piloted aircraft system (RPAS) is evaluated for mapping seasonal snow depth across an alpine basin. RPAS photogrammetry performs well at providing maps of snow depth at high spatial resolution, outperforming field measurements for resolving spatial variability. Uncertainty and error analysis reveal limitations and potential pitfalls of photogrammetric surface-change analysis. Ultimately, RPAS can be a useful tool for understanding snow processes and improving snow modelling efforts.
C. Mulsow, R. Kenner, Y. Bühler, A. Stoffel, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 739–744, https://doi.org/10.5194/isprs-archives-XLII-2-739-2018, https://doi.org/10.5194/isprs-archives-XLII-2-739-2018, 2018
Lucas Davaze, Antoine Rabatel, Yves Arnaud, Pascal Sirguey, Delphine Six, Anne Letreguilly, and Marie Dumont
The Cryosphere, 12, 271–286, https://doi.org/10.5194/tc-12-271-2018, https://doi.org/10.5194/tc-12-271-2018, 2018
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About 150 of the 250 000 inventoried glaciers are currently monitored with surface mass balance (SMB) measurements. To increase this number, we propose a method to retrieve annual and summer SMB from optical satellite imagery, with an application over 30 glaciers in the French Alps. Computing the glacier-wide averaged albedo allows us to reconstruct annual and summer SMB of most of the studied glaciers, highlighting the potential of this method to retrieve SMB of unmonitored glaciers.
Karolina Korzeniowska, Yves Bühler, Mauro Marty, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 17, 1823–1836, https://doi.org/10.5194/nhess-17-1823-2017, https://doi.org/10.5194/nhess-17-1823-2017, 2017
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In this study, we have focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on aerial imagery using an object-based image analysis (OBIA) approach. We compared the results with manually mapped avalanche polygons, and obtained a user’s accuracy of > 0.9 and a Cohen’s kappa of 0.79–0.85. Testing the method for a larger area of 226.3 km2, we estimated producer’s and user’s accuracies of 0.61 and 0.78, respectively.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
Pascal Bohleber, Leo Sold, Douglas R. Hardy, Margit Schwikowski, Patrick Klenk, Andrea Fischer, Pascal Sirguey, Nicolas J. Cullen, Mariusz Potocki, Helene Hoffmann, and Paul Mayewski
The Cryosphere, 11, 469–482, https://doi.org/10.5194/tc-11-469-2017, https://doi.org/10.5194/tc-11-469-2017, 2017
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Our study is the first to use ground-penetrating radar (GPR) to investigate ice thickness and internal layering at Kilimanjaro’s largest ice body, the Northern Ice Field (NIF). For monitoring the ongoing ice loss, our ice thickness soundings allowed us to estimate the total ice volume remaining at NIF's southern portion. Englacial GPR reflections indicate undisturbed layers within NIF's center and provide a first link between age information obtained from ice coring and vertical wall sampling.
Cesar Vera Valero, Nander Wever, Yves Bühler, Lukas Stoffel, Stefan Margreth, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 16, 2303–2323, https://doi.org/10.5194/nhess-16-2303-2016, https://doi.org/10.5194/nhess-16-2303-2016, 2016
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Simulating medium–small avalanches operationally on a mine service road allows avalanche hazard to be assessed on the mine transportation route. Using accurate data from the snow cover and the avalanche paths, the avalanche dynamic model developed can calculate the avalanche runout distances and snow volumes of the deposits. The model does not predict whether the avalanche is coming or not, but if it comes, the model will predict runout distances and mass of the deposits.
Pascal Sirguey, Holly Still, Nicolas J. Cullen, Marie Dumont, Yves Arnaud, and Jonathan P. Conway
The Cryosphere, 10, 2465–2484, https://doi.org/10.5194/tc-10-2465-2016, https://doi.org/10.5194/tc-10-2465-2016, 2016
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Fourteen years of satellite observations are used to monitor the albedo of Brewster Glacier, New Zealand and estimate annual and seasonal balances. This confirms the governing role of the summer balance in the annual balance and allows the reconstruction of the annual balance to 1977 using a photographic record of the snowline. The longest mass balance record for a New Zealand glacier shows negative balances after 2008, yielding a loss of 35 % of the gain accumulated over the previous 30 years.
Yves Bühler, Marc S. Adams, Ruedi Bösch, and Andreas Stoffel
The Cryosphere, 10, 1075–1088, https://doi.org/10.5194/tc-10-1075-2016, https://doi.org/10.5194/tc-10-1075-2016, 2016
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We map the distribution of snow depth at two alpine test sites with unmanned aerial system (UAS) data by applying structure-from-motion photogrammetry. In comparison with manual snow depth measurements, we find high accuracies of 7 to 15 cm for the snow depth values. We can prove that photogrammetric measurements on snow-covered terrain are possible. Underlaying vegetation such as bushes and grass leads to an underestimation of snow depth in the range of 10 to 50 cm.
C. Vera Valero, Y. Bühler, and P. Bartelt
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-2883-2015, https://doi.org/10.5194/nhessd-3-2883-2015, 2015
Manuscript not accepted for further review
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Wet snow avalanches can initiate from large fracture slabs or small point releases. Point
release wet snow avalanches can reach dangerous proportions when they initiate on steep and long avalanche paths and entrain warm moist snow. In this paper we investigate the dynamics of point release wet snow avalanches by applying a numerical model to simulate documented case studies on high altitude slopes in the Chilean Andes. The model simulated correctly flow height, velocity and avalanche run out.
F. Brun, M. Dumont, P. Wagnon, E. Berthier, M. F. Azam, J. M. Shea, P. Sirguey, A. Rabatel, and Al. Ramanathan
The Cryosphere, 9, 341–355, https://doi.org/10.5194/tc-9-341-2015, https://doi.org/10.5194/tc-9-341-2015, 2015
Y. Bühler, M. Marty, L. Egli, J. Veitinger, T. Jonas, P. Thee, and C. Ginzler
The Cryosphere, 9, 229–243, https://doi.org/10.5194/tc-9-229-2015, https://doi.org/10.5194/tc-9-229-2015, 2015
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We are able to map snow depth over large areas ( > 100km2) using airborne digital photogrammetry. Digital photogrammetry is more economical than airborne Laser Scanning but slightly less accurate. Comparisons to independent snow depth measurements reveal an accuracy of about 30cm. Spatial continuous mapping of snow depth is a major step forward compared to point measurements usually applied today. Limitations are steep slopes (> 50°) and areas covered by trees and scrubs.
T. Grünewald, Y. Bühler, and M. Lehning
The Cryosphere, 8, 2381–2394, https://doi.org/10.5194/tc-8-2381-2014, https://doi.org/10.5194/tc-8-2381-2014, 2014
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Elevation dependencies of snow depth are analysed based on snow depth maps obtained from airborne remote sensing. Elevation gradients are characterised by a specific shape: an increase of snow depth with elevation is followed by a distinct peak at a certain level and a decrease in the highest elevations. We attribute this shape to an increase of precipitation with altitude, which is modified by topographical-induced redistribution processes of the snow on the ground (wind, gravitation).
A. Aydin, Y. Bühler, M. Christen, and I. Gürer
Nat. Hazards Earth Syst. Sci., 14, 1145–1154, https://doi.org/10.5194/nhess-14-1145-2014, https://doi.org/10.5194/nhess-14-1145-2014, 2014
C. L. Stevens, P. Sirguey, G. H. Leonard, and T. G. Haskell
The Cryosphere, 7, 1333–1337, https://doi.org/10.5194/tc-7-1333-2013, https://doi.org/10.5194/tc-7-1333-2013, 2013
Y. Bühler, S. Kumar, J. Veitinger, M. Christen, A. Stoffel, and Snehmani
Nat. Hazards Earth Syst. Sci., 13, 1321–1335, https://doi.org/10.5194/nhess-13-1321-2013, https://doi.org/10.5194/nhess-13-1321-2013, 2013
N. J. Cullen, P. Sirguey, T. Mölg, G. Kaser, M. Winkler, and S. J. Fitzsimons
The Cryosphere, 7, 419–431, https://doi.org/10.5194/tc-7-419-2013, https://doi.org/10.5194/tc-7-419-2013, 2013
M. Dumont, J. Gardelle, P. Sirguey, A. Guillot, D. Six, A. Rabatel, and Y. Arnaud
The Cryosphere, 6, 1527–1539, https://doi.org/10.5194/tc-6-1527-2012, https://doi.org/10.5194/tc-6-1527-2012, 2012
Related subject area
Discipline: Snow | Subject: Remote Sensing
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia
Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar
Temporal stability of long-term satellite and reanalysis products to monitor snow cover trends
Towards long-term records of rain-on-snow events across the Arctic from satellite data
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval
Evaluation of E3SM land model snow simulations over the western United States
Landsat, MODIS, and VIIRS snow cover mapping algorithm performance as validated by airborne lidar datasets
Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar
Brief communication: A continuous formulation of microwave scattering from fresh snow to bubbly ice from first principles
Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing
Automated avalanche mapping from SPOT 6/7 satellite imagery with deep learning: results, evaluation, potential and limitations
Exploring the Use of Multi-source High-Resolution Satellite Data for Snow Water Equivalent Reconstruction over Mountainous Catchments
Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation
Snow water equivalent change mapping from slope-correlated synthetic aperture radar interferometry (InSAR) phase variations
Sentinel-1 time series for mapping snow cover depletion and timing of snowmelt in Arctic periglacial environments: case study from Zackenberg and Kobbefjord, Greenland
Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals
Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements
Brief communication: Evaluation of the snow cover detection in the Copernicus High Resolution Snow & Ice Monitoring Service
Evaluation of snow extent time series derived from Advanced Very High Resolution Radiometer global area coverage data (1982–2018) in the Hindu Kush Himalayas
Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements
Impact of dynamic snow density on GlobSnow snow water equivalent retrieval accuracy
The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study
The retrieval of snow properties from SLSTR Sentinel-3 – Part 2: Results and validation
Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States
Mapping avalanches with satellites – evaluation of performance and completeness
Estimating fractional snow cover from passive microwave brightness temperature data using MODIS snow cover product over North America
Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies
Simulating optical top-of-atmosphere radiance satellite images over snow-covered rugged terrain
Parameterizing anisotropic reflectance of snow surfaces from airborne digital camera observations in Antarctica
Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data
Improving sub-canopy snow depth mapping with unmanned aerial vehicles: lidar versus structure-from-motion techniques
Use of Sentinel-1 radar observations to evaluate snowmelt dynamics in alpine regions
Comparison of modeled snow properties in Afghanistan, Pakistan, and Tajikistan
Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals
Regional influence of ocean–atmosphere teleconnections on the timing and duration of MODIS-derived snow cover in British Columbia, Canada
Estimating snow depth on Arctic sea ice using satellite microwave radiometry and a neural network
Suitability analysis of ski areas in China: an integrated study based on natural and socioeconomic conditions
Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards
Monitoring snow depth change across a range of landscapes with ephemeral snowpacks using structure from motion applied to lightweight unmanned aerial vehicle videos
Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry
On the reflectance spectroscopy of snow
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
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We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
Vasana Dharmadasa, Christophe Kinnard, and Michel Baraër
The Cryosphere, 17, 1225–1246, https://doi.org/10.5194/tc-17-1225-2023, https://doi.org/10.5194/tc-17-1225-2023, 2023
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This study highlights the successful usage of UAV lidar to monitor small-scale snow depth distribution. Our results show that underlying topography and wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. This emphasizes the importance of including and better representing these processes in physically based models for accurate snowpack estimates.
Ruben Urraca and Nadine Gobron
The Cryosphere, 17, 1023–1052, https://doi.org/10.5194/tc-17-1023-2023, https://doi.org/10.5194/tc-17-1023-2023, 2023
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We evaluate the fitness of some of the longest satellite (NOAA CDR, 1966–2020) and reanalysis (ERA5, 1950–2020; ERA5-Land, 1950–2020) products currently available to monitor the Northern Hemisphere snow cover trends using 527 stations as the reference. We found different artificial trends and stepwise discontinuities in all the products that hinder the accurate monitoring of snow trends, at least without bias correction. The study also provides updates on the snow cover trends during 1950–2020.
Annett Bartsch, Helena Bergstedt, Georg Pointner, Xaver Muri, Kimmo Rautiainen, Leena Leppänen, Kyle Joly, Aleksandr Sokolov, Pavel Orekhov, Dorothee Ehrich, and Eeva Mariatta Soininen
The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, https://doi.org/10.5194/tc-17-889-2023, 2023
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Rain-on-snow (ROS) events occur across many regions of the terrestrial Arctic in mid-winter. In extreme cases ice layers form which affect wildlife, vegetation and soils beyond the duration of the event. The fusion of multiple types of microwave satellite observations is suggested for the creation of a climate data record. Retrieval is most robust in the tundra biome, where records can be used to identify extremes and the results can be applied to impact studies at regional scale.
Pinja Venäläinen, Kari Luojus, Colleen Mortimer, Juha Lemmetyinen, Jouni Pulliainen, Matias Takala, Mikko Moisander, and Lina Zschenderlein
The Cryosphere, 17, 719–736, https://doi.org/10.5194/tc-17-719-2023, https://doi.org/10.5194/tc-17-719-2023, 2023
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Snow water equivalent (SWE) is a valuable characteristic of snow cover. In this research, we improve the radiometer-based GlobSnow SWE retrieval methodology by implementing spatially and temporally varying snow densities into the retrieval procedure. In addition to improving the accuracy of SWE retrieval, varying snow densities were found to improve the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
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We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Timbo Stillinger, Karl Rittger, Mark S. Raleigh, Alex Michell, Robert E. Davis, and Edward H. Bair
The Cryosphere, 17, 567–590, https://doi.org/10.5194/tc-17-567-2023, https://doi.org/10.5194/tc-17-567-2023, 2023
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Understanding global snow cover is critical for comprehending climate change and its impacts on the lives of billions of people. Satellites are the best way to monitor global snow cover, yet snow varies at a finer spatial resolution than most satellite images. We assessed subpixel snow mapping methods across a spectrum of conditions using airborne lidar. Spectral-unmixing methods outperformed older operational methods and are ready to to advance snow cover mapping at the global scale.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Ghislain Picard, Henning Löwe, and Christian Mätzler
The Cryosphere, 16, 3861–3866, https://doi.org/10.5194/tc-16-3861-2022, https://doi.org/10.5194/tc-16-3861-2022, 2022
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Microwave satellite observations used to monitor the cryosphere require radiative transfer models for their interpretation. These models represent how microwaves are scattered by snow and ice. However no existing theory is suitable for all types of snow and ice found on Earth. We adapted a recently published generic scattering theory to snow and show how it may improve the representation of snows with intermediate densities (~500 kg/m3) and/or with coarse grains at high microwave frequencies.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Elisabeth D. Hafner, Patrick Barton, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 16, 3517–3530, https://doi.org/10.5194/tc-16-3517-2022, https://doi.org/10.5194/tc-16-3517-2022, 2022
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Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-146, https://doi.org/10.5194/tc-2022-146, 2022
Revised manuscript accepted for TC
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The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source data, in-situ observations and a degree-day melting model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the geomorphological features as well as with a reference product. Being able to also reproduce inter-annual variability, the method has great potentiality for hydrological and ecological applications.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Andreas Schmitt, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere, 16, 2163–2181, https://doi.org/10.5194/tc-16-2163-2022, https://doi.org/10.5194/tc-16-2163-2022, 2022
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Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
Jayson Eppler, Bernhard Rabus, and Peter Morse
The Cryosphere, 16, 1497–1521, https://doi.org/10.5194/tc-16-1497-2022, https://doi.org/10.5194/tc-16-1497-2022, 2022
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We introduce a new method for mapping changes in the snow water equivalent (SWE) of dry snow based on differences between time-repeated synthetic aperture radar (SAR) images. It correlates phase differences with variations in the topographic slope which allows the method to work without any "reference" targets within the imaged area and without having to numerically unwrap the spatial phase maps. This overcomes the key challenges faced in using SAR interferometry for SWE change mapping.
Sebastian Buchelt, Kirstine Skov, Kerstin Krøier Rasmussen, and Tobias Ullmann
The Cryosphere, 16, 625–646, https://doi.org/10.5194/tc-16-625-2022, https://doi.org/10.5194/tc-16-625-2022, 2022
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In this paper, we present a threshold and a derivative approach using Sentinel-1 synthetic aperture radar time series to capture the small-scale heterogeneity of snow cover (SC) and snowmelt. Thereby, we can identify start of runoff and end of SC as well as perennial snow and SC extent during melt with high spatiotemporal resolution. Hence, our approach could support monitoring of distribution patterns and hydrological cascading effects of SC from the catchment scale to pan-Arctic observations.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
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To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Christopher Donahue, S. McKenzie Skiles, and Kevin Hammonds
The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, https://doi.org/10.5194/tc-16-43-2022, 2022
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The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Xiaodan Wu, Kathrin Naegeli, Valentina Premier, Carlo Marin, Dujuan Ma, Jingping Wang, and Stefan Wunderle
The Cryosphere, 15, 4261–4279, https://doi.org/10.5194/tc-15-4261-2021, https://doi.org/10.5194/tc-15-4261-2021, 2021
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We performed a comprehensive accuracy assessment of an Advanced Very High Resolution Radiometer global area coverage snow-cover extent time series dataset for the Hindu Kush Himalayan (HKH) region. The sensor-to-sensor consistency, the accuracy related to snow depth, elevations, land-cover types, slope, and aspects, and topographical variability were also explored. Our analysis shows an overall accuracy of 94 % in comparison with in situ station data, which is the same with MOD10A1 V006.
Pia Nielsen-Englyst, Jacob L. Høyer, Kristine S. Madsen, Rasmus T. Tonboe, Gorm Dybkjær, and Sotirios Skarpalezos
The Cryosphere, 15, 3035–3057, https://doi.org/10.5194/tc-15-3035-2021, https://doi.org/10.5194/tc-15-3035-2021, 2021
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The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic ice-covered areas is heavily under-sampled when it comes to in situ measurements. This paper presents a method for estimating daily mean 2 m air temperatures (T2m) in the Arctic from satellite observations of skin temperature, providing spatially detailed observations of the Arctic. The satellite-derived T2m product covers clear-sky snow and ice surfaces in the Arctic for the period 2000–2009.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Linlu Mei, Vladimir Rozanov, Christine Pohl, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2757–2780, https://doi.org/10.5194/tc-15-2757-2021, https://doi.org/10.5194/tc-15-2757-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 1 of two companion papers and shows the method description and sensitivity study. The paper investigates the major factors, including the assumptions of snow optical properties, snow particle distribution and atmospheric conditions (cloud and aerosol), impacting snow property retrievals from satellite observation.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Jennifer M. Jacobs, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, Elizabeth A. Burakowski, Christina Herrick, and Eunsang Cho
The Cryosphere, 15, 1485–1500, https://doi.org/10.5194/tc-15-1485-2021, https://doi.org/10.5194/tc-15-1485-2021, 2021
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This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to map shallow snowpack (< 20 cm) depth in open terrain and forests. The 1 m2 resolution snow depth map, generated by subtracting snow-off from snow-on lidar-derived digital terrain models, consistently had 0.5 to 1 cm precision in the field, with a considerable reduction in accuracy in the forest. Performance depends on the point cloud density and the ground surface variability and vegetation.
Elisabeth D. Hafner, Frank Techel, Silvan Leinss, and Yves Bühler
The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, https://doi.org/10.5194/tc-15-983-2021, 2021
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Satellites prove to be very valuable for documentation of large-scale avalanche periods. To test reliability and completeness, which has not been satisfactorily verified before, we attempt a full validation of avalanches mapped from two optical sensors and one radar sensor. Our results demonstrate the reliability of high-spatial-resolution optical data for avalanche mapping, the suitability of radar for mapping of larger avalanches and the unsuitability of medium-spatial-resolution optical data.
Xiongxin Xiao, Shunlin Liang, Tao He, Daiqiang Wu, Congyuan Pei, and Jianya Gong
The Cryosphere, 15, 835–861, https://doi.org/10.5194/tc-15-835-2021, https://doi.org/10.5194/tc-15-835-2021, 2021
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Daily time series and full space-covered sub-pixel snow cover area data are urgently needed for climate and reanalysis studies. Due to the fact that observations from optical satellite sensors are affected by clouds, this study attempts to capture dynamic characteristics of snow cover at a fine spatiotemporal resolution (daily; 6.25 km) accurately by using passive microwave data. We demonstrate the potential to use the passive microwave and the MODIS data to map the fractional snow cover area.
Marco Bongio, Ali Nadir Arslan, Cemal Melih Tanis, and Carlo De Michele
The Cryosphere, 15, 369–387, https://doi.org/10.5194/tc-15-369-2021, https://doi.org/10.5194/tc-15-369-2021, 2021
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The capability of time-lapse photography to retrieve snow depth time series was tested. We demonstrated that this method can be efficiently used in three different case studies: two in the Italian Alps and one in a forested region of Finland, with an accuracy comparable to the most common methods such as ultrasonic sensors or manual measurements. We hope that this simple method based only on a camera and a graduated stake can enable snow depth measurements in dangerous and inaccessible sites.
Maxim Lamare, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud
The Cryosphere, 14, 3995–4020, https://doi.org/10.5194/tc-14-3995-2020, https://doi.org/10.5194/tc-14-3995-2020, 2020
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Terrain features found in mountainous regions introduce large errors into the calculation of the physical properties of snow using optical satellite images. We present a new model performing rapid calculations of solar radiation over snow-covered rugged terrain that we tested over a site in the French Alps. The results of the study show that all the interactions between sunlight and the terrain should be accounted for over snow-covered surfaces to correctly estimate snow properties from space.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 14, 3959–3978, https://doi.org/10.5194/tc-14-3959-2020, https://doi.org/10.5194/tc-14-3959-2020, 2020
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The angular reflection of solar radiation by snow surfaces is particularly anisotropic and highly variable. We measured the angular reflection from an aircraft using a digital camera in Antarctica in 2013/14 and studied its variability: the anisotropy increases with a lower Sun but decreases for rougher surfaces and larger snow grains. The applied methodology allows for a direct comparison with satellite observations, which generally underestimated the anisotropy measured within this study.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
The Cryosphere, 14, 1919–1935, https://doi.org/10.5194/tc-14-1919-2020, https://doi.org/10.5194/tc-14-1919-2020, 2020
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Unmanned-aerial-vehicle-based (UAV) structure-from-motion (SfM) techniques have the ability to map snow depths in open areas. Here UAV lidar and SfM are compared to map sub-canopy snowpacks. Snow depth accuracy was assessed with data from sites in western Canada collected in 2019. It is demonstrated that UAV lidar can measure the sub-canopy snow depth at a high accuracy, while UAV-SfM cannot. UAV lidar promises to quantify snow–vegetation interactions at unprecedented accuracy and resolution.
Carlo Marin, Giacomo Bertoldi, Valentina Premier, Mattia Callegari, Christian Brida, Kerstin Hürkamp, Jochen Tschiersch, Marc Zebisch, and Claudia Notarnicola
The Cryosphere, 14, 935–956, https://doi.org/10.5194/tc-14-935-2020, https://doi.org/10.5194/tc-14-935-2020, 2020
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In this paper, we use for the first time the synthetic aperture radar (SAR) time series acquired by Sentinel-1 to monitor snowmelt dynamics in alpine regions. We found that the multitemporal SAR allows the identification of the three phases that characterize the melting process, i.e., moistening, ripening and runoff, in a spatial distributed way. We believe that the presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.
Edward H. Bair, Karl Rittger, Jawairia A. Ahmad, and Doug Chabot
The Cryosphere, 14, 331–347, https://doi.org/10.5194/tc-14-331-2020, https://doi.org/10.5194/tc-14-331-2020, 2020
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Ice and snowmelt feed the Indus River and Amu Darya, but validation of estimates from satellite sensors has been a problem until recently, when we were given daily snow depth measurements from these basins. Using these measurements, estimates of snow on the ground were created and compared with models. Estimates of water equivalent in the snowpack were mostly in agreement. Stratigraphy was also modeled and showed 1 year with a relatively stable snowpack but another with multiple weak layers.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Alexandre R. Bevington, Hunter E. Gleason, Vanessa N. Foord, William C. Floyd, and Hardy P. Griesbauer
The Cryosphere, 13, 2693–2712, https://doi.org/10.5194/tc-13-2693-2019, https://doi.org/10.5194/tc-13-2693-2019, 2019
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We investigate the influence of ocean–atmosphere teleconnections on the start, end, and duration of snow cover in British Columbia, Canada. We do this using daily satellite imagery from 2002 to 2018 and assess the accuracy of our methods using reported snow cover at 60 weather stations. We found that there are very strong relationships that vary by region and elevation. This improves our understanding of snow cover distribution and could be used to predict snow cover from ocean–climate indices.
Anne Braakmann-Folgmann and Craig Donlon
The Cryosphere, 13, 2421–2438, https://doi.org/10.5194/tc-13-2421-2019, https://doi.org/10.5194/tc-13-2421-2019, 2019
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Snow on sea ice is a fundamental climate variable. We propose a novel approach to estimate snow depth on sea ice from satellite microwave radiometer measurements at several frequencies using neural networks (NNs). We evaluate our results with airborne snow depth measurements and compare them to three other established snow depth algorithms. We show that our NN results agree better with the airborne data than the other algorithms. This is also advantageous for sea ice thickness calculation.
Jie Deng, Tao Che, Cunde Xiao, Shijin Wang, Liyun Dai, and Akynbekkyzy Meerzhan
The Cryosphere, 13, 2149–2167, https://doi.org/10.5194/tc-13-2149-2019, https://doi.org/10.5194/tc-13-2149-2019, 2019
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The Chinese ski industry is rapidly booming driven by enormous market demand and government support with the coming 2022 Beijing Winter Olympics. We evaluate the locational suitability of ski areas in China by integrating the natural and socioeconomic conditions. Corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.
Isobel R. Lawrence, Michel C. Tsamados, Julienne C. Stroeve, Thomas W. K. Armitage, and Andy L. Ridout
The Cryosphere, 12, 3551–3564, https://doi.org/10.5194/tc-12-3551-2018, https://doi.org/10.5194/tc-12-3551-2018, 2018
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In this paper we estimate the thickness of snow cover on Arctic sea ice from space. We use data from two radar altimeter satellites, AltiKa and CryoSat-2, that have been operating synchronously since 2013. We produce maps of monthly average snow depth for the four growth seasons (October to April): 2012–2013, 2013–2014, 2014–2015, and 2015–2016. Snow depth estimates are essential for the accurate retrieval of sea ice thickness from satellite altimetry.
Richard Fernandes, Christian Prevost, Francis Canisius, Sylvain G. Leblanc, Matt Maloley, Sarah Oakes, Kiyomi Holman, and Anders Knudby
The Cryosphere, 12, 3535–3550, https://doi.org/10.5194/tc-12-3535-2018, https://doi.org/10.5194/tc-12-3535-2018, 2018
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The use of lightweight UAV-based surveys of surface elevation to map snow depth and weekly snow depth change was evaluated over five study areas spanning a range of topography and vegetation cover. Snow depth was estimated with an accuracy of better than 10 cm in the vertical and 3 cm in the horizontal. Vegetation in the snow-free elevation map was a major source of error. As a result, the snow depth change between two dates with snow cover was estimated with an accuracy of better than 4 cm.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, https://doi.org/10.5194/tc-12-3477-2018, 2018
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A remotely piloted aircraft system (RPAS) is evaluated for mapping seasonal snow depth across an alpine basin. RPAS photogrammetry performs well at providing maps of snow depth at high spatial resolution, outperforming field measurements for resolving spatial variability. Uncertainty and error analysis reveal limitations and potential pitfalls of photogrammetric surface-change analysis. Ultimately, RPAS can be a useful tool for understanding snow processes and improving snow modelling efforts.
Alexander Kokhanovsky, Maxim Lamare, Biagio Di Mauro, Ghislain Picard, Laurent Arnaud, Marie Dumont, François Tuzet, Carsten Brockmann, and Jason E. Box
The Cryosphere, 12, 2371–2382, https://doi.org/10.5194/tc-12-2371-2018, https://doi.org/10.5194/tc-12-2371-2018, 2018
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This work presents a new technique with which to derive the snow microphysical and optical properties from snow spectral reflectance measurements. The technique is robust and easy to use, and it does not require the extraction of snow samples from a given snowpack. It can be used in processing satellite imagery over extended fresh dry, wet and polluted snowfields.
Stefan Härer, Matthias Bernhardt, Matthias Siebers, and Karsten Schulz
The Cryosphere, 12, 1629–1642, https://doi.org/10.5194/tc-12-1629-2018, https://doi.org/10.5194/tc-12-1629-2018, 2018
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The paper presents an approach which can be used to process satellite-based snow cover maps with a higher-than-today accuracy at the local scale. Many of the current satellite-based snow maps are using the NDSI with a threshold as a tool for deciding if there is snow on the ground or not. The presented study has shown that, firstly, using the standard threshold of 0.4 can result in significant derivations at the local scale and that, secondly, the deviations become smaller for coarser scales.
Cited articles
Agisoft LLC: Agisoft Metashape User Manual Professional Edition, 1.5, availabe at: https://www.agisoft.com/pdf/photoscan-pro_1_4_en.pdf (last access: 25 October 2019), 2019.
Avanzi, F., Bianchi, A., Cina, A., De Michele, C., Maschio, P., Pagliari,
D., Passoni, D., Pinto, L., Piras, M., and Rossi, L.: Centimetric Accuracy
in Snow Depth Using Unmanned Aerial System Photogrammetry and a
MultiStation, Remote Sens.-Basel, 10, 5,
https://doi.org/10.3390/rs10050765, 2018.
Baggi, S. and Schweizer, J.: Characteristics of wet-snow avalanche
activity: 20 years of observations from a high alpine valley (Dischma,
Switzerland), Nat. Hazards, 50, 97–108,
https://doi.org/10.1007/s11069-008-9322-7, 2008.
Bartelt, P., Buser, O., Vera Valero, C., and Bühler, Y.: Configurational
energy and the formation of mixed flowing/powder snow and ice avalanches,
Ann. Glaciol., 57, 179–188,
https://doi.org/10.3189/2016AoG71A464, 2016.
Basnet, K., Muste, M., Constantinescu, G., Ho, H., and Xu, H.: Close range
photogrammetry for dynamically tracking drifted snow deposition, Cold Reg.
Sci. Technol., 121, 141–153,
https://doi.org/10.1016/j.coldregions.2015.08.013, 2016.
Benassi, F., Dall'Asta, E., Diotri, F., Forlani, G., di Cella, U. M.,
Roncella, R., and Santise, M.: Testing Accuracy and Repeatability of UAV
Blocks Oriented with GNSS-Supported Aerial Triangulation, Remote
Sens.-Basel, 9, 172, https://doi.org/10.3390/rs9020172, 2017.
Beyer, R. A., Alexandrov, O., and McMichael, S.: The Ames Stereo Pipeline:
NASA's Open Source Software for Deriving and Processing Terrain Data, Earth
Space Sci., 5, 537–548,
https://doi.org/10.1029/2018EA000409, 2018.
Bilodeau, F., Gauthier, G., and Berteaux, D.: The effect of snow cover on
lemming population cycles in the Canadian high Arctic, Oecologia, 172,
1007–1016, https://doi.org/10.1007/s00442-012-2549-8, 2013.
Boesch, R., Buhler, Y., Marty, M., and Ginzler, C.: Comparison of digital
surface models for snow depth mapping with UAV and aerial cameras, Int. Arch.
Photogramm., 41, 453–458,
https://doi.org/10.5194/isprs-archives-XLI-B8-453-2016, 2016.
Bühler, Y., Hüni, A., Christen, M., Meister, R., and Kellenberger,
T.: Automated detection and mapping of avalanche deposits using airborne
optical remote sensing data, Cold Reg. Sci. Technol., 57, 99–106,
https://doi.org/10.1016/j.coldregions.2009.02.007, 2009.
Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry, The Cryosphere, 9, 229–243, https://doi.org/10.5194/tc-9-229-2015, 2015.
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075–1088, https://doi.org/10.5194/tc-10-1075-2016, 2016.
Bühler, Y., Adams, M. S., Stoffel, A., and Boesch, R.: Photogrammetric
reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery, Int. J. Remote Sens., 38, 3135–3158,
https://doi.org/10.1080/01431161.2016.1275060, 2017.
Bühler, Y., Hafner, E. D., Zweifel, B., Zesiger, M., and Heisig, H.: Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13, 3225–3238, https://doi.org/10.5194/tc-13-3225-2019, 2019.
Christen, M., Kowalski, J., and Bartelt, P.: RAMMS: Numerical simulation of
dense snow avalanches in three-dimensional terrain, Cold Reg. Sci. Technol.,
63, 1–14, https://doi.org/10.1016/j.coldregions.2010.04.005,
2010.
Cimoli, E., Marcer, M., Vandecrux, B., Bøggild, C. E., Williams, G., and
Simonsen, S. B.: Application of Low-Cost UASs and Digital Photogrammetry for
High-Resolution Snow Depth Mapping in the Arctic, Remote Sens.-Basel, 9, 11,
https://doi.org/10.3390/rs9111144, 2017.
Cullen, N. J., Anderson, B., Sirguey, P., Stumm, D., Mackintosh, A., Conway,
J. P., Horgan, H. J., Dadic, R., Fitzsimons, S. J., and Lorrey, A.: An
11-year record of mass balance of Brewster Glacier, New Zealand, determined
using a geostatistical approach, J. Glaciol., 63, 199–217,
https://doi.org/10.1017/jog.2016.128, 2016.
d'Angelo, P.: Improving Semi-Global Matching: Cost Aggregation and
Confidence Measure, Int. Arch. Photogramm.,
XLI-B1, 299–304,
https://doi.org/10.5194/isprs-archives-XLI-B1-299-2016, 2016.
Deems, J. S. and Painter, T. H.: LiDAR measurement of snow depth: Accuracy
and error sources, in: Proceedings of the 2006 International Snow Science
Workshop, 3–7 October 2016, Telluride, CO, USA, 330–338, 2006.
Deems, J. S., Painter, T. H., and Finnegan, D. C.: Lidar measurement of snow
depth: a review, J. Glaciol., 59, 467–479,
https://doi.org/10.3189/2013JoG12J154, 2013.
De Michele, C., Avanzi, F., Passoni, D., Barzaghi, R., Pinto, L., Dosso, P., Ghezzi, A., Gianatti, R., and Della Vedova, G.: Using a fixed-wing UAS to map snow depth distribution: an evaluation at peak accumulation, The Cryosphere, 10, 511–522, https://doi.org/10.5194/tc-10-511-2016, 2016.
Deschamps-Berger, C., Gascoin, S., Berthier, E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M.: Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data, The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, 2020.
Dong, C.: Remote sensing, hydrological modeling and in situ observations in
snow cover research: A review, J. Hydrol., 561, 573–583,
https://doi.org/10.1016/j.jhydrol.2018.04.027, 2018.
Dreier, L., Bühler, Y., Ginzler, C., and Bartelt, P.: Comparison of
simulated powder snow avalanches with photogrammetric measurements, Ann.
Glaciol., 57, 371–381, https://doi.org/10.3189/2016AoG71A532,
2016.
Eberhard, L. A., Bühler, Y., Marty, M., and Sirguey, P.: Photogrammetric snow depth maps from satellite-, airplane-, UAS and terrestrial platforms from the Davos region (Switzerland), EnviDat, https://doi.org/10.16904/envidat.189, 2020.
Eker, R., Bühler, Y., Schlögl, S., Stoffel, A., and Aydın, A.:
Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote
Sensing Datasets, Remote Sens.-Basel, 11, 6,
https://doi.org/10.3390/rs11060699, 2019.
Farinotti, D., Usselmann,
S., Huss,
M., Bauder,
A., and Funk,
M.: Runoff evolution in the Swiss Alps: projections for selected high-alpine catchments based on ENSEMBLES scenarios, Hydrol. Process., 26, 1909–1924, 2012.
Feistl, T., Bebi, P., Dreier, L., Hanewinkel, M., and Bartelt, P.: Quantification of basal friction for technical and silvicultural glide-snow avalanche mitigation measures, Nat. Hazards Earth Syst. Sci., 14, 2921–2931, https://doi.org/10.5194/nhess-14-2921-2014, 2014.
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung, D. M., Nishimura, K., Satyawali, P. K., and Sokratov, S. A.: The International classification for seasonal snow on the ground, IACS, UNESCO, Paris, France, 2009.
Gascoin, S., Kinnard, C., Ponce, R., Lhermitte, S., MacDonell, S., and Rabatel, A.: Glacier contribution to streamflow in two headwaters of the Huasco River, Dry Andes of Chile, The Cryosphere, 5, 1099–1113, https://doi.org/10.5194/tc-5-1099-2011, 2011.
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software Library, Open Source Geospatial Foundation, available at: https://gdal.org (last access: 15 March 2020), 2020.
Griessinger, N., Mohr, F., and Jonas, T.: Measuring snow ablation rates in
alpine terrain with a mobile multioffset ground-penetrating radar system,
Hydrol. Process., 32, 3272–3282,
https://doi.org/10.1002/hyp.13259, 2018.
Harder, P., Schirmer, M., Pomeroy, J., and Helgason, W.: Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle, The Cryosphere, 10, 2559–2571, https://doi.org/10.5194/tc-10-2559-2016, 2016.
Hirschmuller, H.: Stereo processing by semiglobal matching and mutual
information, IEEE T. Pattern Anal., 30, 328–341,
https://doi.org/10.1109/TPAMI.2007.1166, 2008.
Höhle, J. and Höhle, M.: Accuracy assessment of digital elevation
models by means of robust statistical methods, ISPRS J. Photogramm., 64,
398–406, https://doi.org/10.1016/j.isprsjprs.2009.02.003, 2009.
Hopkinson, C., Demuth, M., Sitar, M., and Chasmer, L.: Applications of airborne LiDAR mapping in glacierised mountainous terrain, IGARSS 2001, Scanning the Present and Resolving the Future. Proceedings, IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), Sydney, NSW, Australia, 2, 949–951, https://doi.org/10.1109/IGARSS.2001.976690, 2001.
Hopkinson, C., Sitar, M., Chasmer, L., and Treitz, P.: Mapping snowpack
depth beneath forest canopies using airborne lidar, Photogramm. Eng. Rem. S., 70, 323–330, https://doi.org/10.14358/PERS.70.3.323, 2004.
Isenburg, M.: LAStools – efficient LiDAR processing software (version 141017, academic), available at: http://rapidlasso.com/LAStools (last access: 15 March 2020), 2014.
Jonas, T., Marty,
C., and Magnusson,
J. O.: Estimating the snow water equivalent from snow depth measurements in the Swiss Alps, J. Hydrol., 378, 161–167, 2009.
Korzeniowska, K., Bühler, Y., Marty, M., and Korup, O.: Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery, Nat. Hazards Earth Syst. Sci., 17, 1823–1836, https://doi.org/10.5194/nhess-17-1823-2017, 2017.
Lato, M. J., Frauenfelder, R., and Bühler, Y.: Automated detection of snow avalanche deposits: segmentation and classification of optical remote sensing imagery, Nat. Hazards Earth Syst. Sci., 12, 2893–2906, https://doi.org/10.5194/nhess-12-2893-2012, 2012.
Lopez-Moreno, J. I., Revuelto, J., Alonso-Gonzalez, E., Sanmiguel-Vallelado,
A., Fassnacht, S. R., Deems, J., and Moran-Tejeda, E.: Using very long-range
terrestrial laser scanner to analyze the temporal consistency of the
snowpack distribution in a high mountain environment, J. Mt. Sci.-Engl., 14,
823–842, https://doi.org/10.1007/s11629-016-4086-0, 2017.
Luhmann, T., Robson, S., Kyle, S., and Boehm, J.: Close-Range Photogrammetry
and 3D Imaging, 2 ed., edited by: Luhmann, T., Robson, S., Kyle, S.,
and Boehm, J., De Gruyter, Berlin, Germany and Boston, USA, 2014.
Lundberg, A., Granlund, N., and Gustafsson, D.: Towards automated “Ground
truth” snow measurements – a review of operational and new measurement methods
for Sweden, Norway, and Finland, Hydrol. Process., 24, 1955–1970,
https://doi.org/10.1002/hyp.7658, 2010.
Marti, R., Gascoin, S., Berthier, E., de Pinel, M., Houet, T., and Laffly, D.: Mapping snow depth in open alpine terrain from stereo satellite imagery, The Cryosphere, 10, 1361–1380, https://doi.org/10.5194/tc-10-1361-2016, 2016.
Maune, D. F. and Naygandhi, A.: Digital Elevation Model Technologies and
Applications: The DEM Users Manual, 3 ed., edited by: Maune, D. F. and
Naygandhi, A., American Society for Photogrammetry and Remote Sensing, Maryland,
USA, 2018.
McGrath, D., Sass, L., O'Neel, S., Arendt, A., Wolken, G., Gusmeroli, A.,
Kienholz, C., and McNeil, C.: End-of-winter snow depth variability on
glaciers in Alaska, J. Geophys. Res-Earth, 120, 1530–1550,
https://doi.org/10.1002/2015JF003539, 2015.
McGrath, D., Webb, R., Shean, D., Bonnell, R., Marshall, H. P., Painter, T.
H., Molotch, N. P., Elder, K., Hiemstra, C., and Brucker, L.: Spatially
Extensive Ground-Penetrating Radar Snow Depth Observations During NASA's
2017 SnowEx Campaign: Comparison With In Situ, Airborne, and Satellite
Observations, Water Resour. Res., 55, 10026–10036,
https://doi.org/10.1029/2019WR024907, 2019.
Meyer, J. and Skiles, S. M.: Assessing the Ability of Structure From Motion
to Map High-Resolution Snow Surface Elevations in Complex Terrain: A Case
Study From Senator Beck Basin, CO, Water Resour. Res., 55, 6596–6605,
https://doi.org/10.1029/2018WR024518, 2019.
Nolan, M., Larsen, C., and Sturm, M.: Mapping snow depth from manned aircraft on landscape scales at centimeter resolution using structure-from-motion photogrammetry, The Cryosphere, 9, 1445–1463, https://doi.org/10.5194/tc-9-1445-2015, 2015.
Novac, J.: Quality assessment of elevation data, in: Digital Elevation Model
Technologies and Applications: The DEM Users Manual, 3rd Edition,
edited by: Maune, D. F. and Nayegandhi, A., American Society for Photogrammetry and Remote Sensing, Maryland,
USA, 455–544, 2018.
Painter, T. H., Berisford, D. F., Boardman, J. W., Bormann, K. J., Deems, J.
S., Gehrke, F., Hedrick, A., Joyce, M., Laidlaw, R., Marks, D., Mattmann,
C., McGurk, B., Ramirez, P., Richardson, M., Skiles, S. M., Seidel, F. C.,
and Winstral, A.: The Airborne Snow Observatory: Fusion of scanning lidar,
imaging spectrometer, and physically-based modeling for mapping snow water
equivalent and snow albedo, Remote Sens. Environ., 184, 139–152, https://doi.org/10.1016/j.rse.2016.06.018, 2016.
Prokop, A.: Assessing the applicability of terrestrial laser scanning for
spatial snow depth measurements, Cold Reg. Sci. Technol., 54, 155–163,
https://doi.org/10.1016/j.coldregions.2008.07.002, 2008.
Prokop, A., Schon, P., Singer, F., Pulfer, G., Naaim, M., Thibert, E., and
Soruco, A.: Merging terrestrial laser scanning technology with
photogrammetric and total station data for the determination of avalanche
modeling parameters, Cold Reg. Sci. Technol., 110, 223–230,
https://doi.org/10.1016/j.coldregions.2014.11.009, 2015.
Redpath, T. A. N., Sirguey, P., and Cullen, N. J.: Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry, The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, 2018.
Roze, A., Zufferey,
J.-C., Beyeler, and McClellan,
A.
A.: eBee RTK Accuracy Assessment, White Paper, available at: https://www.sensefly.com/app/uploads/2017/11/eBee_RTK_Accuracy_Assessment.pdf (last access: 2 December 2019), 2017.
Schlatter, A. and Marti, U.: Höhentransformation zwischen LHN95 und den
Gebrauchshöhen LN02, Geomatik Schweiz: Geoinformation und Landmanagement, 103, 450–453, https://doi.org/10.5169/seals-236251, 2005.
Schön, P., Prokop, A., Vionnet, V., Guyomarc'h, G., Naaim-Bouvet, F.,
and Heiser, M.: Improving a terrain-based parameter for the assessment of
snow depths with TLS data in the Col du Lac Blanc area, Cold Reg. Sci.
Technol., 114, 15–26,
https://doi.org/10.1016/j.coldregions.2015.02.005, 2015.
Shaw, T. E., Gascoin, S., Mendoza, P. A., Pellicciotti, F., and McPhee, J.:
Snow Depth Patterns in a High Mountain Andean Catchment from Satellite
Optical Tristereoscopic Remote Sensing, Water Resour. Res., 56, 2,
https://doi.org/10.1029/2019WR024880, 2020.
Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R.,
Porter, C., and Morin, P.: An automated, open-source pipeline for mass
production of digital elevation models (DEMs) from very-high-resolution
commercial stereo satellite imagery, ISPRS J. Photogramm., 116, 101–117,
https://doi.org/10.1016/j.isprsjprs.2016.03.012, 2016.
Sirguey, P. and Cullen, N. J.: A very high resolution DEM of Kilimanjaro via
photogrammetry of GeoEye-1 images (KILISoSDEM2012), New Zealand Institute of Surveyors, Wellington, N.Z., 19–215, ISSN 0048-0150,
2014.
Spandre, P., François, H., Thibert, E., Morin, S., and George-Marcelpoil, E.: Determination of snowmaking efficiency on a ski slope from observations and modelling of snowmaking events and seasonal snow accumulation, The Cryosphere, 11, 891–909, https://doi.org/10.5194/tc-11-891-2017, 2017.
Steiner, L., Meindl, M., Fierz, C., and Geiger, A.: An assessment of sub-snow GPS for quantification of snow water equivalent, The Cryosphere, 12, 3161–3175, https://doi.org/10.5194/tc-12-3161-2018, 2018.
Stumpf, A., Malet, J. P., Allemand, P., and Ulrich, P.: Surface
reconstruction and landslide displacement measurements with Pléiades
satellite images, ISPRS J. Photogramm., 95, 1–12,
https://doi.org/10.1016/j.isprsjprs.2014.05.008, 2014.
Sturm, M. and Holmgren, J.: An Automatic Snow Depth Probe for Field
Validation Campaigns, Water Resour. Res., 54, 9695–9701,
https://doi.org/10.1029/2018WR023559, 2018.
Sturm, M., Derksen, C., Liston, G., Silis, A., Solie, D., Holm-
gren, J., and Huntington, H.: A reconnaissance snow survey
across northwest territories and Nunavut, Canada, April 2007,
Cold Regions Research and Engineering laboratory, Hanover,
N.H.ERDC/CRREL TR 08-3, 1–80, 2008.
Telling, J., Lyda, A., Hartzell, P., and Glennie, C.: Review of Earth
science research using terrestrial laser scanning, Earth-Sci. Rev.,
169, 35–68, https://doi.org/10.1016/j.earscirev.2017.04.007,
2017.
Thibert, E., Bellot, H., Ravanat, X., Ousset, F., Pulfer, G., Naaim, M.,
Hagenmuller, P., Naaim-Bouvet, F., Faug, T., Nishimura, K., Ito, Y.,
Baroudi, D., Prokop, A., Schon, P., Soruco, A., Vincent, C., Limam, A., and
Heno, R.: The full-scale avalanche test-site at Lautaret Pass (French Alps),
Cold Reg. Sci. Technol., 115, 30–41,
https://doi.org/10.1016/j.coldregions.2015.03.005, 2015.
Toth, C. and Jozkow, G.: Remote sensing platforms and sensors: A survey,
ISPRS J. Photogramm., 115, 22–36,
https://doi.org/10.1016/j.isprsjprs.2015.10.004, 2016.
Vallet, J., Gruber, U., and Dufour, F.: Photogrammetric avalanche volume
measurements at Vallee de la Sionne, Switzerland, Ann. Glaciol., 32,
141–146, https://doi.org/10.1016/j.isprsjprs.2015.10.004, 2001.
Vallet, J., Turnbull, B., Joly, S., and Dufour, F.: Observations on powder
snow avalanches using videogrammetry, Cold Reg. Sci. Technol., 39, 153–159,
https://doi.org/10.1016/j.coldregions.2004.05.004, 2004.
Vander Jagt, B., Lucieer, A., Wallace, L., Turner, D., and Durand, M.: Snow
Depth Retrieval with UAS Using Photogrammetric Techniques, Geosciences, 5,
264–285, https://doi.org/10.3390/geosciences5030264, 2015.
Walter, B., Huwald, H., Gehring, J., Bühler, Y., and Lehning, M.: Radar measurements of blowing snow off a mountain ridge, The Cryosphere, 14, 1779–1794, https://doi.org/10.5194/tc-14-1779-2020, 2020.
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., and
Reynolds, J. M.: “Structure-from-Motion” photogrammetry: A low-cost,
effective tool for geoscience applications, Geomorphology, 179, 300–314,
https://doi.org/10.1016/j.geomorph.2012.08.021, 2012.
Wipf, S., Stoeckli, V., and Bebi, P.: Winter climate change in alpine
tundra: plant responses to changes in snow depth and snowmelt timing,
Climatic Change, 94, 105–121,
https://doi.org/10.1007/s10584-009-9546-x, 2009.
Short summary
In spring 2018 in the alpine Dischma valley (Switzerland), we tested different industrial photogrammetric platforms for snow depth mapping. These platforms were high-resolution satellites, an airplane, unmanned aerial systems and a terrestrial system. Therefore, this study gives a general overview of the accuracy and precision of the different photogrammetric platforms available in space and on earth and their use for snow depth mapping.
In spring 2018 in the alpine Dischma valley (Switzerland), we tested different industrial...