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Special Issue "Remote Sensing of Glaciers at Global and Regional Scales"

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 (28 February 2019)

Special Issue Editors

Guest Editor
Dr. Bert Wouters

Utrecht University, Department of Physics, Institute for Marine and Atmospheric Research (IMAU),P.O. Box 80.005 , 3508 TA Utrecht, The Netherlands
Website | E-Mail
Interests: glaciology; mass balance; remote sensing; altimetry; gravimetry; modelling
Guest Editor
Dr. Alex Gardner

Jet Propulsion Laboratory, California Institute of Technology,4800 Oak Grove Drive, Pasadena, CA 91109, USA
Website | E-Mail
Phone: 818-354-3177
Interests: glaciology; feature tracking; altimetry; mass change; remote sensing
Guest Editor
Dr. Stef Lhermitte

Delft University of Technology, Dept. of Geoscience & Remote Sensing, Stevinweg 1, 2628 CN Delft, Netherlands
Website | E-Mail
Interests: remote sensing; snow and ice surface properties; land–atmosphere interactions; glaciology
Guest Editor
Dr. Geir Moholdt

Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway
Website | E-Mail
Phone: +47 77750658
Interests: remote sensing; altimetry; glaciology; mass balance; Arctic; Antarctica

Special Issue Information

Dear Colleagues,

Mountain glaciers and ice-caps are often nicknamed ‘nature's thermometers’. Because of their relatively small size and high mass turnover rates, they show a rapid response to changes in the climate, and are one of the most visible indicators of a changing climate. Retreat and shrinkage of glaciers have been globally observed over the last century, and comes with profound societal, economic and environmental impacts, such as the release of freshwater into the oceans, glacier lake outbursts and landslides, and changes in local water availability for water consumption, hydro-electric power generation, agriculture and irrigation.

The total amount of ice stored in glaciers and ice caps is only a small fraction (~1%) of the volume of the vast Greenland and Antarctic Ice Sheets. Yet, in the latest IPCC report, they were estimated to be the single largest land contributor to sea level rise in the 20th century, accounting for about 0.7 mm/y between 1901 and 1990. Until the mid-2000s, such estimates were mainly based on extrapolation of a limited number of in situ observations of relatively small glaciers, often located in easily accessible locations with a maritime climate, which comes with large uncertainties.

The advent of satellite remote sensing has led to a leap forward in our understanding of the state of the cryosphere as it provides regular, near-global coverage of the Earth's glaciated regions. In this Special Issue, we invite contributions focusing on recent and upcoming advances in the application of satellite remote sensing to monitoring changes in the state of the Earth's mountain glaciers and ice caps. This excludes the main ice sheets of Antarctica and Greenland, but we do welcome studies focusing on their peripheral glaciers and ice caps, including the Antarctic Peninsula. Potential topics include, but are not limited to:

  • variations in the volume and mass of glacier regions from gravimetry, altimetry, photogrammetry, etc.
  • changes in their extent and surface properties (such as surface albedo)
  • changes in the flow behavior of glacier regions, e.g., surface velocity and discharge
  • first results from recently launched satellites (e.g., ESA's Sentinels) and the potential of upcoming missions (e.g., ICESat-2, GRACE-FO)
  • multi-platform merging and the combination of satellite observations with historical data sources
  • integration and assimilation of satellite remote sensing data into Earth system models
  • novel applications of data processing, such as machine learning and “big data” analysis
Dr. Bert Wouters
Dr. Alex Gardner
Dr. Stef Lhermitte
Dr. Geir Moholdt
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 papers will be 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 1800 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

  • Glacier changes
  • Glacier mass balance
  • Glacier elevation and volume changes
  • Glacier flow velocities and discharge
  • Glacier extent and surface properties
  • Multi-platform merging
  • Optical and microwave imaging
  • Gravimetry, altimetry, photogrammetry, SAR
  • Recently launched and upcoming mission

Published Papers (6 papers)

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Research

Open AccessArticle
Spatially Variable Glacier Changes in the Annapurna Conservation Area, Nepal, 2000 to 2016
Remote Sens. 2019, 11(12), 1452; https://doi.org/10.3390/rs11121452
Received: 21 May 2019 / Revised: 5 June 2019 / Accepted: 13 June 2019 / Published: 19 June 2019
PDF Full-text (8443 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Himalayan glaciers have shrunk rapidly in recent decades, but the spatial pattern of ice loss is highly variable and appears to be modulated by factors relating to individual glacier characteristics. This hinders our ability to predict their future evolution, which is vital for [...] Read more.
Himalayan glaciers have shrunk rapidly in recent decades, but the spatial pattern of ice loss is highly variable and appears to be modulated by factors relating to individual glacier characteristics. This hinders our ability to predict their future evolution, which is vital for water resource management. The aim of this study is to assess recent glacier changes in the little-studied Annapurna Conservation Area (ACA; area: 7629 km2) in Nepal, and to explore local controls influencing their behaviour. We map changes in glacier area, surface elevation, and ice flow velocity on a large sample of glaciers (n = 162) in the ACA between 2000 and 2016. We found that total glacier area decreased by 8.5% between 2000 and 2014/15. Ice surface velocity changes between 2002 and 2016 were variable, with no clear trend of acceleration or deceleration. The mean surface elevation change for a smaller sample of glaciers (n = 72) was −0.33 ± 0.22 m a−1 between 2000 and 2013/16, which equates to a mean mass balance of −0.28 ± 0.24 m w.e. a−1. There was a trend of increasingly less negative mass balance towards the north. Glaciers that lost the most mass in the north of the ACA tended to have lower maximum elevations, bottom-heavy hypsometries, and were more likely to be avalanche-fed. However, these patterns were not apparent in glaciers in central ACA. There was no significant difference in the mean surface elevation change rate on the ablation zones of debris-covered compared with debris-free glaciers. Our work shows that glaciers in the ACA are losing area and mass at variable rates, but that the influence of local controls is complex, which introduces large uncertainties when predicting their future evolution. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Graphical abstract

Open AccessArticle
On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data
Remote Sens. 2019, 11(12), 1410; https://doi.org/10.3390/rs11121410
Received: 17 April 2019 / Revised: 29 May 2019 / Accepted: 7 June 2019 / Published: 14 June 2019
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Abstract
Mapping snow cover (SC) on glaciers at the end of the ablation period provides a possibility to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is a metric for the mass balance. Satellite determination of glacier snow cover, [...] Read more.
Mapping snow cover (SC) on glaciers at the end of the ablation period provides a possibility to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is a metric for the mass balance. Satellite determination of glacier snow cover, derived over large regions, can reveal its spatial variability and temporal trends. Accordingly, snow mapping on glaciers has been widely applied using several satellite sensors. However, as glacier ice originates from compressed snow, both have very similar spectral properties and standard methods to map snow struggle to distinguish snow on glaciers. Hence, most studies applied manual delineation of snow extent on glaciers. Here we present an automated tool, named ‘ASMAG’ (automated snow mapping on glaciers), to map SC on glaciers and derive the related snow line altitude (SLA) for individual glaciers using multi-temporal Landsat satellite imagery and a digital elevation model (DEM). The method has been developed using the example of the Ötztal Alps, where an evaluation of the method is possible using field-based observations of the annual equilibrium line altitude (ELA) and the accumulation area ratio (AAR) measured for three glaciers for more than 30 years. The tool automatically selects a threshold to map snow on glaciers and robustly calculates the SLA based on the frequency distribution of elevation bins with more than 50% SC. The accuracy of the SC mapping was about 90% and the SLA was determined successfully in 80% of all cases with a mean uncertainty of ±19 m. When cloud-free scenes close to the date of the highest snowline are available, a good to very good agreement of SC ratios (SCR)/SLA with field data of AAR/ELA are obtained, otherwise values are systematically higher/lower as useful images were often acquired too early in the summer season. However, glacier specific differences are still well captured. Snow mapping on glaciers is impeded by clouds and their shadows or when fresh snow is covering the glaciers, so that more frequent image acquisitions (as now provided by Sentinel-2) would improve results. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Open AccessArticle
Quality Assessment and Glaciological Applications of Digital Elevation Models Derived from Space-Borne and Aerial Images over Two Tidewater Glaciers of Southern Spitsbergen
Remote Sens. 2019, 11(9), 1121; https://doi.org/10.3390/rs11091121
Received: 28 February 2019 / Revised: 4 May 2019 / Accepted: 7 May 2019 / Published: 10 May 2019
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Abstract
In this study, we assess the accuracy and precision of digital elevation models (DEM) retrieved from aerial photographs taken in 2011 and from Very High Resolution satellite images (WorldView-2 and Pléiades) from the period 2012–2017. Additionally, the accuracy of the freely available Strip [...] Read more.
In this study, we assess the accuracy and precision of digital elevation models (DEM) retrieved from aerial photographs taken in 2011 and from Very High Resolution satellite images (WorldView-2 and Pléiades) from the period 2012–2017. Additionally, the accuracy of the freely available Strip product of ArcticDEM was verified. We use the DEMs to characterize geometry changes over Hansbreen and Hornbreen, two tidewater glaciers in southern Spitsbergen, Svalbard. The satellite-based DEMs from WorldView-2 and Pléiades stereo pairs were processed using the Rational Function Model (RFM) without and with one ground control point. The elevation quality of the DEMs over glacierized areas was validated with in situ data: static differential GPS survey of mass balance stakes and GPS kinematic data acquired during ground penetrating radar survey. Results demonstrate the usefulness of the analyzed sources of DEMs for estimation of the total geodetic mass balance of the Svalbard glaciers. DEM accuracy is sufficient to investigate glacier surface elevation changes above 1 m. Strips from the ArcticDEM are generally precise, but some of them showed gross errors and need to be handled with caution. The surface of Hansbreen and Hornbreen has been lowering in recent years. The average annual elevation changes for Hansbreen were more negative in the period 2015–2017 (−2.4 m a−1) than in the period 2011–2015 (−1.7 m a−1). The average annual elevation changes over the studied area of Hornbreen for the period 2012–2017 amounted to −1.6 m a−1. The geodetic mass balance for Hansbreen was more negative than the climatic mass balance estimated using the mass budget method, probably due to underestimation of the ice discharge. From 2011 to 2017, Hansbreen lost on average over 1% of its volume each year. Such a high rate of relative loss illustrates how fast these glaciers are responding to climate change. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Graphical abstract

Open AccessArticle
Glacier Facies Mapping Using a Machine-Learning Algorithm: The Parlung Zangbo Basin Case Study
Remote Sens. 2019, 11(4), 452; https://doi.org/10.3390/rs11040452
Received: 21 December 2018 / Revised: 11 February 2019 / Accepted: 18 February 2019 / Published: 22 February 2019
Cited by 1 | PDF Full-text (10532 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Glaciers in the Tibetan Plateau are an important indicator of climate change. Automatic glacier facies mapping utilizing remote sensing data is challenging due to the spectral similarity of supraglacial debris and the adjacent bedrock. Most of the available glacier datasets do not provide [...] Read more.
Glaciers in the Tibetan Plateau are an important indicator of climate change. Automatic glacier facies mapping utilizing remote sensing data is challenging due to the spectral similarity of supraglacial debris and the adjacent bedrock. Most of the available glacier datasets do not provide the boundary of clean ice and debris-covered glacier facies, while debris-covered glacier facies play a key role in mass balance research. The aim of this study was to develop an automatic algorithm to distinguish ice cover types based on multi-temporal satellite data, and the algorithm was implemented in a subregion of the Parlung Zangbo basin in the southeastern Tibetan Plateau. The classification method was built upon an automated machine learning approach: Random Forest in combination with the analysis of topographic and textural features based on Landsat-8 imagery and multiple digital elevation model (DEM) data. Very high spatial resolution Gao Fen-1 (GF-1) Panchromatic and Multi-Spectral (PMS) imagery was used to select training samples and validate the classification results. In this study, all of the land cover types were classified with overall good performance using the proposed method. The results indicated that fully debris-covered glaciers accounted for approximately 20.7% of the total glacier area in this region and were mainly distributed at elevations between 4600 m and 4800 m above sea level (a.s.l.). Additionally, an analysis of the results clearly revealed that the proportion of small size glaciers (<1 km2) were 88.3% distributed at lower elevations compared to larger size glaciers (≥1 km2). In addition, the majority of glaciers (both in terms of glacier number and area) were characterized by a mean slope ranging between 20° and 30°, and 42.1% of glaciers had a northeast and north orientation in the Parlung Zangbo basin. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Graphical abstract

Open AccessArticle
Pléiades Tri-Stereo Data for Glacier Investigations—Examples from the European Alps and the Khumbu Himal
Remote Sens. 2018, 10(10), 1563; https://doi.org/10.3390/rs10101563
Received: 21 June 2018 / Revised: 19 September 2018 / Accepted: 25 September 2018 / Published: 29 September 2018
Cited by 3 | PDF Full-text (77140 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we use Pléiades tri-stereo data to generate a digital elevation model (DEM) from the Pléiades images using a workflow employing semi-global matching (SGM). We examine the DEM accuracy in complex mountain glaciated terrain by comparing the new DEMs with an [...] Read more.
In this study, we use Pléiades tri-stereo data to generate a digital elevation model (DEM) from the Pléiades images using a workflow employing semi-global matching (SGM). We examine the DEM accuracy in complex mountain glaciated terrain by comparing the new DEMs with an independent high-quality DEM based on airborne laser scanning (ALS) data for a study area in the Austrian Alps, and with ground control points for a study area in the Khumbu Himal of Nepal. The DEMs derived using the SGM algorithm compare well to the independent high-quality ALS DEM, and the workflow produces models of sufficient quality to resolve ground control points, which are based on Pléiades imagery that are of sufficient quality to perform high spatio-temporal resolution assessments of remote areas for which no field data is available. The relative accuracy is sufficient to investigate glacier surface elevation changes below one meter, and can therefore be applied over relatively short periods of time, such as those required for annual and seasonal assessments of change. The annual geodetic mass balance for the Alpine case derived from our DEM compares well to the glaciological mass balance, and multitemporal DEM analysis is used to resolve the seasonal changes of five glaciers in the Khumbu Himal, revealing that glaciological processes such as accumulation, ablation, and glacier movement mainly take place during the summer season, with the winter season being largely inactive in the year sampled. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Graphical abstract

Open AccessArticle
Annual Glacier-Wide Mass Balance (2000–2016) of the Interior Tibetan Plateau Reconstructed from MODIS Albedo Products
Remote Sens. 2018, 10(7), 1031; https://doi.org/10.3390/rs10071031
Received: 18 April 2018 / Revised: 8 June 2018 / Accepted: 28 June 2018 / Published: 30 June 2018
PDF Full-text (5413 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Glaciers in the Tibetan Plateau (TP) play a crucial role in regulating agriculture irrigation, river discharge and the regional/global climate system. However, mass balance records of TP glaciers have remained scarce due to challenging mountainous terrain and harsh weather conditions, which limits our [...] Read more.
Glaciers in the Tibetan Plateau (TP) play a crucial role in regulating agriculture irrigation, river discharge and the regional/global climate system. However, mass balance records of TP glaciers have remained scarce due to challenging mountainous terrain and harsh weather conditions, which limits our understanding of the influence of melting glaciers on local water resources and responses to climate change. Here, we present and assess an albedo-based method to derive annual mass balance for three glaciers in the interior TP from Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data during 2000–2016. A strong linear correlation (R2 = 0.941, P < 0.001) is found between annual minimum-averaged glacier-wide albedo (AMGA) values and annual mass balance measurements on the Xiao Dongkemadi glacier. Furthermore, the 17-year-long annual mass balance series of the Xiao Dongkemadi glacier and the Geladandong mountain region glaciers, and the Purogangri ice cap are reconstructed for the first time, with a mass loss rate of 535 ± 63 mm w.e.a−1, 243 ± 66 mm w.e.a−1 and 113 ± 68 mm w.e.a−1, respectively. The results are verified by geodetic estimates, with relative error ranging from 4.55% to 11.80%, confirming that the albedo-based method can be used to estimate specific mass budgets for interior TP glaciers. A strong correlation between the mass balance series and air temperature infers that increasing summer air temperature may be one of main reasons for glacier shrinkage of the three studied glaciers. Full article
(This article belongs to the Special Issue Remote Sensing of Glaciers at Global and Regional Scales)
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Graphical abstract

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