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Applications of Remote Sensing in Glaciology

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 55388

Special Issue Editors

School of Geosciences, University of Aberdeen, King’s College, Aberdeen AB24 3UE, UK
Interests: remote sensing applications in land dynamics; landforms and surface processes on Mars; glacial and periglacial geomorphology; glacial hazards; Mars analogue research; high-resolution terrain modelling and interpretation; UAVs for environmental remote sensing
Special Issues, Collections and Topics in MDPI journals
School of Geosciences, University of Aberdeen, Aberdeen AB24 3FX, UK
Interests: remote sensing; glaciology; cryosphere; physical geography; terrain modelling; land cover changes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Glaciers are well-established climate change indicators, and their continuous monitoring is imperative for understanding the complexities of glacio–climatic interactions. Although the importance of glaciers as climate proxies was first recognized in the latter half of the 19th century, the awareness about glacier monitoring for climate change assessment has persistently increased since 1990, after the Intergovernmental Panel on Climate Change (IPCC) started to include glacier fluctuation data in their assessments. Large-scale shifts in the areal, altitudinal, and flow regimes of glaciers are bound to promote glacial disasters and hydrological irregularities at regional scales, necessitating their worldwide monitoring. Year-round, field-based glacier monitoring is limited by several factors, such as a hostile climate, poor approachability, and inadequate skilled labor and funding. In such scenarios, remote sensing is largely utilized as a practical alternative or a supporting technique to field studies, in order to meet the growing needs of glaciological research.

With the continuous advancements in imaging systems and remote sensing platforms, and enhancements in the computational efficiencies of hardware and related software programs, the number of research applications in glaciology has considerably increased in the recent years. Many universities have started dedicated programs or courses in glaciology, and well-known international remote sensing journals have increased the frequency of Special Issues covering glaciological or cryospheric research.

This topical collection invites multidisciplinary submissions pertaining to the use of remote sensing in assessing glacier changes and the associated impacts in high altitude/high latitude regions, and provides a wide scope so as to contribute in all areas of contemporary/future glaciological research. The Special Issue is not only limited to terrestrial glacial landforms, but will be equally interesting for planetary researchers working on the ice–debris complexes or other glacial geomorphological aspects of planets such as Mars. The topics can be related (but not restricted) to the use of spaceborne/aerial/terrestrial remote sensing for glacier mapping, glacier area changes, volumetric estimations, glacio-hydrology, glacier flow dynamics, glacial or periglacial geomorphology, glacial lakes, glacial seismology, lithological mapping in a glacial environment, glacial hazards, and synergy between glacier field work and remote sensing.

We look forward to your excellent contributions!

Dr. Anshuman Bhardwaj
Dr. Lydia Sam
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • remote sensing
  • glacier mapping
  • glacier area changes
  • volumetric estimations
  • glacio-hydrology
  • glacier flow dynamics
  • glacial or periglacial geomorphology
  • glacial lakes
  • glacial seismology
  • glacial hazards

Published Papers (15 papers)

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Editorial

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4 pages, 198 KiB  
Editorial
Editorial: Applications of Remote Sensing in Glaciology
Remote Sens. 2022, 14(17), 4146; https://doi.org/10.3390/rs14174146 - 23 Aug 2022
Viewed by 1475
Abstract
Contemporary and significant spatiotemporal changes in glaciers are a result of rapidly evolving regional and global climate, and continuous monitoring is imperative for understanding the complexities of glacio–climatic interactions [...] Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)

Research

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22 pages, 8346 KiB  
Article
Machine Learning Approaches to Automatically Detect Glacier Snow Lines on Multi-Spectral Satellite Images
Remote Sens. 2022, 14(16), 3868; https://doi.org/10.3390/rs14163868 - 09 Aug 2022
Cited by 5 | Viewed by 2236
Abstract
Documenting the inter-annual variability and the long-term trend of the glacier snow line altitude is highly relevant to document the evolution of glacier mass changes. Automatically identifying the snow line on glaciers is challenging; recent developments in machine learning approaches show promise to [...] Read more.
Documenting the inter-annual variability and the long-term trend of the glacier snow line altitude is highly relevant to document the evolution of glacier mass changes. Automatically identifying the snow line on glaciers is challenging; recent developments in machine learning approaches show promise to tackle this issue. This manuscript presents a proof of concept of machine learning approaches applied to multi-spectral images to detect the snow line and quantify its average altitude. The tested approaches include the combination of different image processing and classification methods, and takes into account cast shadows. The efficiency of these approaches is evaluated on mountain glaciers in the European Alps by comparing the results with manually annotated data. Solutions provided by the different approaches are robust when compared to the ground truth’s snow lines, with a Pearson’s correlation ranging from 79% to 96% depending on the method. However, the tested approaches may fail when snow lines are not continuous or exhibit a strong change of elevation. The major advantage over the state of the art is that the proposed approach does not require one calibration per glacier. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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16 pages, 6081 KiB  
Article
Quantifying the Artificial Reduction of Glacial Ice Melt in a Mountain Glacier (Urumqi Glacier No. 1, Tien Shan, China)
Remote Sens. 2022, 14(12), 2802; https://doi.org/10.3390/rs14122802 - 10 Jun 2022
Cited by 6 | Viewed by 2223
Abstract
Artificial glacier melt reduction is gaining increasing attention because of rapid glacier retreats and the projected acceleration of future mass losses. However, quantifying the effect of artificial melt reduction on glaciers in China has not been currently reported. Therefore, the case of Urumqi [...] Read more.
Artificial glacier melt reduction is gaining increasing attention because of rapid glacier retreats and the projected acceleration of future mass losses. However, quantifying the effect of artificial melt reduction on glaciers in China has not been currently reported. Therefore, the case of Urumqi Glacier No.1 (eastern Tien Shan, China) is used to conduct a scientific evaluation of glacier cover efficiency for melt reduction between 24 June and 28 August 2021. By combining two high-resolution digital elevation models derived from terrestrial laser scanning and unmanned aerial vehicles, albedo, and meteorological data, glacier ablation mitigation under three different cover materials was assessed. The results revealed that up to 32% of mass loss was preserved in the protected areas compared with that of the unprotected areas. In contrast to the unprotected glacier surface, the nanofiber material reduced the glacier melt by up to 56%, which was significantly higher than that achieved by geotextiles (29%). This outcome could be attributed to the albedo of the materials and local climate factors. The nanofiber material showed higher albedo than the two geotextiles, dirty snow, clean ice, and dirty ice. Although clean snow had a higher albedo than the other materials, its impact on slowing glacier melt was minor due to the lower snowfall and relatively high air temperature after snowfall in the study area. This indicates that the efficiencies of nanofiber material and geotextiles can be beneficial in high-mountain areas. In general, the results of our study demonstrate that the high potential of glacier cover can help mitigate issues related to regions of higher glacier melt or lacking water resources, as well as tourist attractions. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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32 pages, 25845 KiB  
Article
Reconstruction and Characterisation of Past and the Most Recent Slope Failure Events at the 2021 Rock-Ice Avalanche Site in Chamoli, Indian Himalaya
Remote Sens. 2022, 14(4), 949; https://doi.org/10.3390/rs14040949 - 16 Feb 2022
Cited by 8 | Viewed by 4514
Abstract
Frequent ice avalanche events are being reported across the globe in recent years. On the 7 February 2021, a flash flood triggered by a rock-ice avalanche with an unusually long runout distance, caused significant damage of life and property in the Tapovan region [...] Read more.
Frequent ice avalanche events are being reported across the globe in recent years. On the 7 February 2021, a flash flood triggered by a rock-ice avalanche with an unusually long runout distance, caused significant damage of life and property in the Tapovan region of the Indian Himalaya. Using multi-temporal satellite datasets, digital terrain models (DTMs) and simulations, here we report the pre-event and during-event flow characteristics of two large-scale avalanches within a 5-year interval at the slope failure site. Prior to both the events, we observed short-term and long-term changes in surface velocity (SV) with maximum SVs increasing up to over 5 times the normal values. We further simulated the events to understand their mechanical characteristics leading to long runouts. In addition to its massive volume, the extraordinary magnitude of the 2021 event can partly be attributed to the possible remobilisation and entrainment of the colluvial deposits from previous ice and snow avalanches. The anomalous SVs should be explored further for their suitability as a possible remotely observable precursor of ice avalanches from hanging glaciers. This sequence of events highlights that there is a need to take into account the antecedent conditions, while making a holistic assessment of the hazard. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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23 pages, 4808 KiB  
Article
Comparing Methods for Segmenting Supra-Glacial Lakes and Surface Features in the Mount Everest Region of the Himalayas Using Chinese GaoFen-3 SAR Images
Remote Sens. 2021, 13(13), 2429; https://doi.org/10.3390/rs13132429 - 22 Jun 2021
Cited by 16 | Viewed by 3117
Abstract
Glaciers and numerous glacial lakes that are produced by glacier melting are key indicators of climate change. Often overlooked, supra-glacial lakes develop in the melting area in the low-lying part of a glacier and appear to be highly variable in their size, shape, [...] Read more.
Glaciers and numerous glacial lakes that are produced by glacier melting are key indicators of climate change. Often overlooked, supra-glacial lakes develop in the melting area in the low-lying part of a glacier and appear to be highly variable in their size, shape, and location. The lifespan of these lakes is thought to be quite transient, since the lakes may be completely filled by water and burst out within several weeks. Changes in supra-glacial lake outlines and other surface features such as supra-glacial rivers and crevasses on the glaciers are useful indicators for the direct monitoring of glacier changes. Synthetic aperture radar (SAR) is not affected by weather and climate, and is an effective tool for study of glaciated areas. The development of the Chinese GaoFen-3 (GF-3) SAR, which has high spatial and temporal resolution and high-precision observation performance, has made it possible to obtain dynamic information about glaciers in more detail. In this paper, the classical Canny operator, the variational B-spline level-set method, and U-Net-based deep-learning model were applied and compared to extract glacial lake outlines and other surface features using different modes and Chinese GF-3 SAR imagery in the Mount Everest Region of the Himalayas. Particularly, the U-Net-based deep-learning method, which was independent of auxiliary data and had a high degree of automation, was used for the first time in this context. The experimental results showed that the U-Net-based deep-learning model worked best in the segmentation of supra-glacial lakes in terms of accuracy (Precision = 98.45% and Recall = 95.82%) and segmentation efficiency, and was good at detecting small, elongated, and ice-covered supra-glacial lakes. We also found that it was useful for accurately identifying the location of supra-glacial streams and ice crevasses on glaciers, and quantifying their width. Finally, based on the time series of the mapping results, the spatial characteristics and temporal evolution of these features over the glaciers were comprehensively analyzed. Overall, this study presents a novel approach to improve the detection accuracy of glacier elements that could be leveraged for dynamic monitoring in future research. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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28 pages, 7207 KiB  
Article
Local- and Regional-Scale Forcing of Glacier Mass Balance Changes in the Swiss Alps
Remote Sens. 2021, 13(10), 1949; https://doi.org/10.3390/rs13101949 - 17 May 2021
Cited by 4 | Viewed by 2471
Abstract
Glacier mass variations are climate indicators. Therefore, it is essential to examine both winter and summer mass balance variability over a long period of time to address climate-related ice mass fluctuations. In this study, we analyze glacier mass balance components and hypsometric characteristics [...] Read more.
Glacier mass variations are climate indicators. Therefore, it is essential to examine both winter and summer mass balance variability over a long period of time to address climate-related ice mass fluctuations. In this study, we analyze glacier mass balance components and hypsometric characteristics with respect to their interactions with local meteorological variables and remote large-scale atmospheric and oceanic patterns. The results show that all selected glaciers have lost their equilibrium condition in recent decades, with persistent negative annual mass balance trends and decreasing accumulation area ratios (AARs), accompanied by increasing air temperatures of ≥ +0.45 °C decade−1. The controlling factor of annual mass balance is mainly attributed to summer mass losses, which are correlated with (warming) June to September air temperatures. In addition, the interannual variability of summer and winter mass balances is primarily associated to the Atlantic Multidecadal Oscillation (AMO), Greenland Blocking Index (GBI), and East Atlantic (EA) teleconnections. Although climate parameters are playing a significant role in determining the glacier mass balance in the region, the observed correlations and mass balance trends are in agreement with the hypsometric distribution and morphology of the glaciers. The analysis of decadal frontal retreat using Landsat images from 1984 to 2014 also supports the findings of this research, highlighting the impact of lake formation at terminus areas on rapid glacier retreat and mass loss in the Swiss Alps. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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29 pages, 15048 KiB  
Article
Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau
Remote Sens. 2021, 13(1), 80; https://doi.org/10.3390/rs13010080 - 28 Dec 2020
Cited by 10 | Viewed by 3299
Abstract
Monitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. [...] Read more.
Monitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. Detailed patterns in glacier surface velocity and its seasonal variability in the PZB are still uncertain, however. We utilized Landsat-8 (L8) OLI data to investigate in detail the variability of glacier velocity in the PZB by applying the normalized image cross-correlation method. On the basis of satellite images acquired from 2013 to 2020, we present a map of time-averaged glacier surface velocity and examined four typical glaciers (Yanong, Parlung No.4, Xueyougu, and Azha) in the PZB. Next, we explored the driving factors of surface velocity and of its variability. The results show that the glacier centerline velocity increased slightly in 2017–2020. The analysis of meteorological data at two weather stations on the outskirts of the glacier area provided some indications of increased precipitation during winter-spring. Such increase likely had an impact on ice mass accumulation in the up-stream portion of the glacier. The accumulated ice mass could have caused seasonal velocity changes in response to mass imbalance during 2017–2020. Besides, there was a clear winter-spring speedup of 40% in the upper glacier region, while a summer speedup occurred at the glacier tongue. The seasonal and interannual velocity variability was captured by the transverse velocity profiles in the four selected glaciers. The observed spatial pattern and seasonal variability in glacier surface velocity suggests that the winter-spring snow might be a driver of glacier flow in the central and upper portions of glaciers. Furthermore, the variations in glacier surface velocity are likely related to topographic setting and basal slip caused by the percolation of rainfall. The findings on glacier velocity suggest that the transfer of winter-spring accumulated ice triggered by mass conservation seems to be the main driver of changes in glacier velocity. The reasons that influence the seasonal surface velocity change need further investigation. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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23 pages, 9265 KiB  
Article
Estimation of Ice Thickness and the Features of Subglacial Media Detected by Ground Penetrating Radar at the Baishui River Glacier No. 1 in Mt. Yulong, China
Remote Sens. 2020, 12(24), 4105; https://doi.org/10.3390/rs12244105 - 16 Dec 2020
Cited by 9 | Viewed by 2490
Abstract
Using ground-penetrating radar (GPR), we measured and estimated the ice thickness of the Baishui River Glacier No. 1 of Yulong Snow Mountain. According to the position of the reflected media from the GPR image, combined with the radar waveform amplitude and polarity change [...] Read more.
Using ground-penetrating radar (GPR), we measured and estimated the ice thickness of the Baishui River Glacier No. 1 of Yulong Snow Mountain. According to the position of the reflected media from the GPR image, combined with the radar waveform amplitude and polarity change information, the ice thickness and the changing medium position at the bottom of this temperate glacier were identified. Water paths were found in the measured ice, including ice caves and crevasses. A debris-rich ice layer was found at the bottom of the glacier, which produces strong abrasion and ploughing action at the bedrock surface. This results in the formation of different detrital layers stagnated at the ice-bedrock interface and numerous crevasses on the bedrock surface. Based on the obtained ice thickness and differential GPS data, combined with Landsat images, the kriging interpolation method was used to obtain grid data. The average ice thickness was 52.48 m and between 4740 and 4890 m above sea level, with a maximum depth of 92.83 m. The bedrock topography map of this area was drawn using digital elevation model from the Shuttle Radar Topography Mission. The central part of the glacier was characterized by small ice basins with distributed ice steps and ice ridges at the upper and lower parts. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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23 pages, 7459 KiB  
Article
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets
Remote Sens. 2020, 12(23), 3917; https://doi.org/10.3390/rs12233917 - 29 Nov 2020
Cited by 7 | Viewed by 3342
Abstract
The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data [...] Read more.
The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study, we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km2 of glacier area in southeast Alaska, USA, covered by two void-free DEMs as the study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier–Stokes and shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric methods) void filling approaches for glacier elevation data sets were implemented and evaluated. The hypsometric approaches showed, in general, the worst performance, leading to high average and local offsets. Telea and Navier–Stokes void filling showed an overall stable and reasonable quality. The best results are obtained for shearlet and bilinear void filling, if certain criteria are met. Considering also computational costs and feasibility, we recommend using the bilinear void filling method in glacier volume change analyses. Moreover, we propose and validate a formula to estimate the uncertainties caused by void filling in glacier volume change computations. The formula is transferable to other study sites, where no ground truth data on the void areas exist, and leads to higher accuracy of the error estimates on void-filled areas. In the spirit of reproducible research, we publish a software repository with the implementation of the novel void filling algorithms and the code reproducing the statistical analysis of the data, along with the data sets themselves. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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25 pages, 6557 KiB  
Article
Change Points Detected in Decadal and Seasonal Trends of Outlet Glacier Terminus Positions across West Greenland
Remote Sens. 2020, 12(21), 3651; https://doi.org/10.3390/rs12213651 - 07 Nov 2020
Cited by 3 | Viewed by 2663
Abstract
We investigated the change in terminus position between 1985 and 2015 of 17 marine-terminating glaciers that drain into Disko and Uummannaq Bays, West Greenland, by manually digitizing over 5000 individual frontal positions from over 1200 Landsat images. We find that 15 of 17 [...] Read more.
We investigated the change in terminus position between 1985 and 2015 of 17 marine-terminating glaciers that drain into Disko and Uummannaq Bays, West Greenland, by manually digitizing over 5000 individual frontal positions from over 1200 Landsat images. We find that 15 of 17 glacier termini retreated over the study period, with ~80% of this retreat occurring since 2000. Increased frequency of Landsat observations since 2000 allowed for further investigation of the seasonal variability in terminus position. We identified 10 actively retreating glaciers based on a significant positive relationship between glaciers with cumulative retreat >300 m since 2000 and their average annual amplitude (seasonal range) in terminus position. Finally, using the Detecting Breakpoints and Estimating Segments in Trend (DBEST) program, we investigated whether the 2000–2015 trends in terminus position were explained by the occurrence of change points (significant trend transitions). Based on the change point analysis, we found that nine of 10 glaciers identified as actively retreating also underwent two or three periods of change, during which their terminus positions were characterized by increases in cumulative retreat. Previous literature suggests potential relationships between our identified change dates with anomalous ocean conditions, such as low sea ice concentration and high sea surface temperatures, and our change durations with individual fjord geometry. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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28 pages, 29388 KiB  
Article
Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application
Remote Sens. 2020, 12(20), 3443; https://doi.org/10.3390/rs12203443 - 20 Oct 2020
Cited by 15 | Viewed by 5467 | Correction
Abstract
Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in [...] Read more.
Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in the past and lake formation in the future. This study uses the available information to predict potential sites for future lake formation in the Upper Rhône catchment located in the Southwestern Swiss Alps. The study integrates the latest available glacier outlines and high-quality digital elevation models (DEMs) into the Volume and Topography Automation (VOLTA) model to estimate ice thickness within the extent of the glaciers. Unlike the previous ice thickness models, VOLTA calculates ice thickness distribution based on automatically-derived centerlines, while optimizing the model by including the valley side drag parameter in the force equation. In this study, a total ice volume of 37.17 ± 12.26 km3 (1σ) was estimated for the Upper Rhône catchment. The comparison of VOLTA performance indicates a stronger relationship between measured and predicted bedrock, confirming the less variability in VOLTA’s results (r2 ≈ 0.92) than Glacier Bed Topography (GlabTop) (r2 ≈ 0.82). Overall, the mean percentage of ice thickness error for all measured profiles in the Upper Rhône catchment is around ±22%, of which 28 out of 42 glaciers are underestimated. By incorporating the vertical accuracy of free-ice DEM, we could identify 171 overdeepenings. Among them, 100 sites have a high potential for future lake formation based on four morphological criteria. The visual evaluation of deglaciated areas also supports the robustness of the presented methodology, as 11 water bodies were already formed within the predicted overdeepenings. In the wake of changing global climate, such results highlight the importance of combined datasets and parameters for projecting the future glacial landscapes. The timely information on future glacial lake formation can equip planners with essential knowledge, not only for managing water resources and hazards, but also for understanding glacier dynamics, catchment ecology, and landscape evolution of high-mountain regions. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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20 pages, 9493 KiB  
Article
Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018
Remote Sens. 2020, 12(13), 2105; https://doi.org/10.3390/rs12132105 - 01 Jul 2020
Cited by 17 | Viewed by 3707
Abstract
Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the [...] Read more.
Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm’s accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 ℃. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 ℃ a−1 during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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20 pages, 8587 KiB  
Article
A Bidirectional Analysis Method for Extracting Glacier Crevasses from Airborne LiDAR Point Clouds
Remote Sens. 2019, 11(20), 2373; https://doi.org/10.3390/rs11202373 - 13 Oct 2019
Cited by 7 | Viewed by 2771
Abstract
A crevasse is an important surface feature of a glacier. This study aims to detect crevasses from high-density airborne LiDAR point clouds. However, existing methods continue to suffer from the data holes within the crevasse region and the influence of the undulating non-crevasse [...] Read more.
A crevasse is an important surface feature of a glacier. This study aims to detect crevasses from high-density airborne LiDAR point clouds. However, existing methods continue to suffer from the data holes within the crevasse region and the influence of the undulating non-crevasse glacier surfaces. Therefore, a bidirectional analysis method is proposed to robustly extract the crevasses from the point clouds, which utilizes their vertical and horizontal characteristics. First, crevasse points are separated from non-crevasse points using a hybrid-entity method, where the height difference and the nearly vertical characteristic of a crevasse sidewall are considered, to better distinguish the crevasses from the undulating non-crevasse glacier surfaces. Second, the crevasse regions/edges are adaptively delineated by a local statistical analysis method that is based on a novel feature of the Delaunay triangulation mesh of non-crevasse points in the horizontal plane. Last, the pseudo-crevasse points and regions are removed by a cross-analysis method. To test the performance of the proposed method, this study selected airborne LiDAR point clouds from two sites of Alaskan glaciers (i.e., Tyndall Glacier and Seward Glacier) as the experimental datasets. The results were verified by a comparison with the ground truth that was manually delineated. The proposed method achieved acceptable results: the recall, precision, and F 1 scores of both sites exceeded 94.00%. Moreover, a comparative experiment was carried out and the results confirmed that the proposed method achieved superior performance. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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Review

Jump to: Editorial, Research

36 pages, 7282 KiB  
Review
The Remotely and Directly Obtained Results of Glaciological Studies on King George Island: A Review
Remote Sens. 2022, 14(12), 2736; https://doi.org/10.3390/rs14122736 - 07 Jun 2022
Cited by 5 | Viewed by 1748
Abstract
Climate warming has become indisputable, and it is now crucial to increase our understanding of both the mechanisms and consequences of climate change. The Antarctic region is subjected to substantial changes, the trends of which have been recognized for several decades. In the [...] Read more.
Climate warming has become indisputable, and it is now crucial to increase our understanding of both the mechanisms and consequences of climate change. The Antarctic region is subjected to substantial changes, the trends of which have been recognized for several decades. In the South Shetland Islands, the most visible effect of climate change is progressive deglaciation. The following review focuses on past glaciological studies conducted on King George Island (KGI). The results of collected cryosphere element observations are discussed herein in a comprehensive manner. Our analysis showed that there is a lack of temporal as well as spatial continuity for studies on the basic mass balance parameters on the entire KGI ice dome and only Bellingshausen Dome has a relatively long history of data collection. The methodologies of past work, which have improved over time, are also discussed. When studying the glacier front fluctuations, the authors most frequently use a 1956 aerial photography as reference ice coverage. This was the case for seven papers, while other sources are seldomly mentioned. In other papers as many as 41 other sources were used, and therefore comparison to photos taken up to 60 years later can give misleading trends, as small glaciers may have both advanced and retreated in that time. In the case of glacial velocities there is also an apparent lack of consistency, as different glaciers were indicated as the fastest on KGI. Only Lange, Anna, Crystal, Eldred, and eastern part of Usher glaciers were determined by more than one author as the fastest. Additionally, there are gaps in the KGI Ground Penetrating Radar (GPR) survey area, which includes three ice domes: the Warszawa Icefield, the Krakow Icefield, and eastern part of King George Island. Ideas for further work on the topic are also suggested, allowing for easier access to data and thus contributing to a better understanding of glacier development mechanisms. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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40 pages, 2089 KiB  
Review
Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects
Remote Sens. 2020, 12(6), 948; https://doi.org/10.3390/rs12060948 - 15 Mar 2020
Cited by 86 | Viewed by 10967
Abstract
Owing to usual logistic hardships related to field-based cryospheric research, remote sensing has played a significant role in understanding the frozen components of the Earth system. Conventional spaceborne or airborne remote sensing platforms have their own merits and limitations. Unmanned aerial vehicles (UAVs) [...] Read more.
Owing to usual logistic hardships related to field-based cryospheric research, remote sensing has played a significant role in understanding the frozen components of the Earth system. Conventional spaceborne or airborne remote sensing platforms have their own merits and limitations. Unmanned aerial vehicles (UAVs) have emerged as a viable and inexpensive option for studying the cryospheric components at unprecedented spatiotemporal resolutions. UAVs are adaptable to various cryospheric research needs in terms of providing flexibility with data acquisition windows, revisits, data/sensor types (multispectral, hyperspectral, microwave, thermal/night imaging, Light Detection and Ranging (LiDAR), and photogrammetric stereos), viewing angles, flying altitudes, and overlap dimensions. Thus, UAVs have the potential to act as a bridging remote sensing platform between spatially discrete in situ observations and spatially continuous but coarser and costlier spaceborne or conventional airborne remote sensing. In recent years, a number of studies using UAVs for cryospheric research have been published. However, a holistic review discussing the methodological advancements, hardware and software improvements, results, and future prospects of such cryospheric studies is completely missing. In the present scenario of rapidly changing global and regional climate, studying cryospheric changes using UAVs is bound to gain further momentum and future studies will benefit from a balanced review on this topic. Our review covers the most recent applications of UAVs within glaciology, snow, permafrost, and polar research to support the continued development of high-resolution investigations of cryosphere. We also analyze the UAV and sensor hardware, and data acquisition and processing software in terms of popularity for cryospheric applications and revisit the existing UAV flying regulations in cold regions of the world. The recent usage of UAVs outlined in 103 case studies provide expertise that future investigators should base decisions on. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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