Articles | Volume 15, issue 3
The Cryosphere, 15, 1485–1500, 2021
https://doi.org/10.5194/tc-15-1485-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Cryosphere, 15, 1485–1500, 2021
https://doi.org/10.5194/tc-15-1485-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
24 Mar 2021
Research article
| 24 Mar 2021
Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States
Jennifer M. Jacobs et al.
Related authors
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, Rhae Sung Kim, and Jennifer M. Jacobs
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-136, https://doi.org/10.5194/hess-2022-136, 2022
Preprint under review for HESS
Short summary
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While land surface models are a common approach for estimating macroscale snow water equivalent (SWE), the SWE accuracy is often limited by uncertainties in model physics and forcing inputs. In this study, we found large underestimations of modeled SWE compared to observations. Precipitation forcings and melting physics limitations dominantly contribute to the SWE underestimations. Results provide insights into prioritizing strategies to improve the SWE simulations for hydrologic applications.
Holly Proulx, Jennifer M. Jacobs, Elizabeth A. Burakowski, Eunsang Cho, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, and Cameron Wagner
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-7, https://doi.org/10.5194/tc-2022-7, 2022
Revised manuscript under review for TC
Short summary
Short summary
This study compares snow depth measurements from two manual instruments and an airborne platform in a field and forest. The manual instruments’ snow depths differed by 1 to 3 cm. The airborne measurements , which do not penetrate the leaf litter, were consistently shallower than either manual instrument. When combining airborne snow depth maps with manual density measurements, corrections may be required to create unbiased maps of snow properties.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, Rhae Sung Kim, and Jennifer M. Jacobs
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-136, https://doi.org/10.5194/hess-2022-136, 2022
Preprint under review for HESS
Short summary
Short summary
While land surface models are a common approach for estimating macroscale snow water equivalent (SWE), the SWE accuracy is often limited by uncertainties in model physics and forcing inputs. In this study, we found large underestimations of modeled SWE compared to observations. Precipitation forcings and melting physics limitations dominantly contribute to the SWE underestimations. Results provide insights into prioritizing strategies to improve the SWE simulations for hydrologic applications.
Holly Proulx, Jennifer M. Jacobs, Elizabeth A. Burakowski, Eunsang Cho, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, and Cameron Wagner
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-7, https://doi.org/10.5194/tc-2022-7, 2022
Revised manuscript under review for TC
Short summary
Short summary
This study compares snow depth measurements from two manual instruments and an airborne platform in a field and forest. The manual instruments’ snow depths differed by 1 to 3 cm. The airborne measurements , which do not penetrate the leaf litter, were consistently shallower than either manual instrument. When combining airborne snow depth maps with manual density measurements, corrections may be required to create unbiased maps of snow properties.
David F. Hill, Elizabeth A. Burakowski, Ryan L. Crumley, Julia Keon, J. Michelle Hu, Anthony A. Arendt, Katreen Wikstrom Jones, and Gabriel J. Wolken
The Cryosphere, 13, 1767–1784, https://doi.org/10.5194/tc-13-1767-2019, https://doi.org/10.5194/tc-13-1767-2019, 2019
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We present a new statistical model for converting snow depths to water equivalent. The only variables required are snow depth, day of year, and location. We use the location to look up climatological parameters such as mean winter precipitation and mean temperature difference (difference between hottest month and coldest month). The model is simple by design so that it can be applied to depth measurements anywhere, anytime. The model is shown to perform better than other widely used approaches.
Related subject area
Discipline: Snow | Subject: Remote Sensing
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
Potential of X-band polarimetric SAR co-polar phase difference for Arctic snow depth estimation
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
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
Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping
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
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.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-314, https://doi.org/10.5194/tc-2021-314, 2021
Revised manuscript accepted for TC
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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 TerraSAR-X satellite. Using a high spatial resolution vegetation classification, we were able to quantify the variability of snow depth as well as the topographic soil wetness index which provided a better understanding of the electromagnetic wave-ground interaction.
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.
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.
Lucie A. Eberhard, Pascal Sirguey, Aubrey Miller, Mauro Marty, Konrad Schindler, Andreas Stoffel, and Yves Bühler
The Cryosphere, 15, 69–94, https://doi.org/10.5194/tc-15-69-2021, https://doi.org/10.5194/tc-15-69-2021, 2021
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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.
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
Adams, M. S., Bühler, Y., and Fromm, R.: Multitemporal accuracy and
precision assessment of unmanned aerial system photogrammetry for
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Short summary
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.
This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to...
