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Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation for Emergency Management".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 15127

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Special Issue Editors

Dr. Dariusz Ignatiuk

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Guest Editor

Faculty of Natural Sciences, University of Silesia in Katowice, Katowice, Poland
Interests: glaciology; snow and glacier hydrology; cryosphere changes; remote sensing; glacier mass and energy balance; UAV and satellite observations; GPR; laser scanner

Dr. Shridhar Jawak

E-Mail Website
Guest Editor

Svalbard Integrated Arctic Earth Observing System (SIOS), SIOS Knowledge Centre, Svalbard Science Centre, P.O. Box 156, N-9171 Longyearbyen, Svalbard, Norway
Interests: cryospheric GIScience and remote sensing; glaciological image analysis; machine learning and deep learning; Earth observation applications in Arctic, Antarctic, and Himalayas; airborne remote sensing
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Special Issue Information

Dear Colleagues,

We invite articles that address satellite observations of the effects of climate change on the glaciers and ice sheets. The accelerating trend of climate warming is causing significant changes in the cryosphere and stimulating faster energy exchange between the atmosphere and glaciers (ice sheets). The observed disparities in meteorological parameters demonstrate regional differences in climate warming and the subsequent response of glaciers. Our ambition is to show these changes taking place in the Earth's cryosphere, as well as processes taking place in the atmosphere that have an impact on glaciers. Our aim is to compile articles showing the latest trends in the use of Earth observation and remote sensing methods for modelling, direct observations and new ideas, in order to understand cryospheric changes. Contributions using new sensors and platforms that consider the integration of datasets or calibration and validation (cal/val) analyses are especially welcome.

Dr. Dariusz Ignatiuk
Dr. Shridhar Jawak
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

ice sheet
ice cap
glacier
snow
remote sensing
numerical modeling of glaciers
glacier and ice sheet mass balance
glacier hydrology and dynamics from remote sensing
satellite observations
Earth observation
glaciological image analysis
Arctic
Antarctic
Himalayas
Greenland
image processing
machine and deep learning applications in glaciology
google earth engine

Published Papers (7 papers)

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19 pages, 14850 KiB

Open AccessArticle

Quantifying Changes in Extent and Velocity of the Hornbreen/Hambergbreen Glacial System (SW, Spitsbergen) Based on Timeseries of Multispectral Satellite Imagery

by Dawid Saferna, Małgorzata Błaszczyk, Mariusz Grabiec and Bogdan Gądek

Remote Sens. 2023, 15(14), 3529; https://doi.org/10.3390/rs15143529 - 13 Jul 2023

Viewed by 1141

Abstract

This study focuses on the Hornsund region in Svalbard, where the temperature has risen by 1.14 °C per decade, six times faster than the global average. The accelerating temperature rise in the Arctic has had significant impacts on the Svalbard glaciers, including the Hornbreen–Hambergbreen system (HH system). The HH system connects Sørkapp Land with the rest of Spitsbergen, and its disintegration will lead to the formation of a new island. This study assesses the annual and seasonal changes in the velocity of the HH system and fluctuations of the position of the termini from 1985 to 2021 and their relationship with environmental factors. Furthermore, an assessment was made of the possible date of opening of the Hornsund strait. The study also investigates the impact of the radiometric resolution of satellite images on the quality of the velocity field and the detection of glacier features. Multispectral imagery was used to assess the velocity fields with Glacier Image Velocimetry (v 1.01) software, which uses the feature tracking method. In addition, the Glacier Termini Tracking plugin was used to acquire data on the fluctuating positions of the termini. The long-term mean annual velocity of the Hornbreen was 431 m a⁻¹, while that of Hambergbreen was 141 m a⁻¹. The peak seasonal velocity and fluctuations of the terminus position of Hambergbreen were delayed by approximately one month when compared to Hornbreen. Overall, air and sea surface temperatures influence the velocities and fluctuations of the termini, while precipitation plays a secondary role. If the recession continues, the Hornsund strait may open around 2053. An increase in the quality of velocity maps from 12.7% to 50.2% was found with an increase in radiometric resolution from 8 bit to 16 bit. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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20 pages, 13586 KiB

Open AccessArticle

Accelerated Glacier Area Loss in the Zhetysu (Dzhungar) Alatau Range (Tien Shan) for the Period of 1956–2016

by Serik Nurakynov, Azamat Kaldybayev, Kanat Zulpykharov, Nurmakhambet Sydyk, Aibek Merekeyev, Daniker Chepashev, Aiman Nyssanbayeva, Gulnura Issanova and Gonghuan Fang

Remote Sens. 2023, 15(8), 2133; https://doi.org/10.3390/rs15082133 - 18 Apr 2023

Viewed by 1190

Abstract

An updated glacier inventory is important for understanding the current glacier dynamics in the conditions of actual accelerating glacier retreat observed around the world. Here, we present a detailed analysis of the glaciation areas of the Zhetysu Alatau Range (Tien Shan) for 1956–2016 using well-established semiautomatic methods based on the band ratios. The total glacier area decreased by 49 ± 2.8% or by 399 ± 11.2 km² from 813.6 ± 22.8 km² to 414.6 ± 11.6 km² during 1956–2016, while the number of glaciers increased from 985 to 813. Similar rates of area change characterized the periods 1956–2001, 2001–2012, 2012–2016, and 2001–2016: −296.2 ± 8.3 (−0.8% a⁻¹), −63.7± 1.8 (−1.1% a⁻¹), −39.1 ±1.1 (−2.2% a⁻¹) and −102.8 ± 2.9 (−1.3% a⁻¹) km², respectively. The mean glacier size decreased from 0.57 km² in 2001 to 0.51 km² in 2016. Most glaciation areas of the Zhetysu Alatau faced north (north, northwest, and northeast), covered 390.35 ± 11 km², and were located in altitudes between 3000 and 4000 m.a.s.l. With shrinkage rates of about −0.8% and −1.3% a⁻¹ for the periods of 1956–2001 and 2001–2016, our results show that study area has the highest shrinkage rate compared to other glacierized areas of Central Asian mountains, including Altai, Pamir, and even the inner ranges of Tien Shan. It was found that a significant increase in temperature (0.12 °C/10 years) plays a main role in the state of glaciers. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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40 pages, 7500 KiB

Open AccessArticle

Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data

by Shridhar D. Jawak, Alvarinho J. Luis, Prashant H. Pandit, Sagar F. Wankhede, Peter Convey and Peter T. Fretwell

Remote Sens. 2023, 15(5), 1287; https://doi.org/10.3390/rs15051287 - 26 Feb 2023

Cited by 5 | Viewed by 2776

Abstract

Mapping spatiotemporal changes in the distribution of blue ice regions (BIRs) in Antarctica requires repeated, precise, and high-resolution baseline maps of the blue ice extent. This study demonstrated the design and application of a newly-developed semi-automatic method to map BIRs in the Antarctic environment using very high-resolution (VHR) WorldView-2 (WV-2) satellite images. We discussed the potential of VHR satellite data for the mapping of BIRs in the Antarctic environment using a customized normalized-difference blue-ice index (NDBI) method devised using yellow, green, and near-infrared spectral bands of WV-2 data. We compared the viability of the newly developed customized NDBI approach against state-of-the-art target detection (TD), spectral processing (SP) and pixel-wise supervised (PSC) feature extraction (FE) approaches. Four semi-automatic FE approaches (three existing plus one newly developed) consisting of 16 standalone FE methods (12 existing + four customized) were evaluated using an extensive quantitative and comparative assessment for mapping BIRs in the vicinity of Schirmacher Oasis, on the continental Antarctic coastline. The results suggested that the customized NDBI approach gave a superior performance and the highest statistical stability when compared with existing FE techniques. The customized NDBI generally rendered the lowest level of misclassification (average RMSE = 654.48 ± 58.26 m²), followed by TD (average RMSE = 987.81 ± 55.05 m²), SP (average RMSE = 1327.09 ± 127.83 m²) and PSC (average RMSE = 2259.43 ± 115.36 m²) for mapping BIRs. Our results indicated that the use of the customized NDBI approach can greatly improve the semi-automatic mapping of BIRs in the Antarctic environment. This study presents the first refined map of distribution of BIRs around the Schirmacher Oasis. The total area of blue ice in the study area was estimated to be 106.875 km², approximately 61% of the study area. The WV-2 derived BIR map area presented in this study locally refined the existing BIR map derived using Landsat Enhanced Thematic Mapper Plus (ETM+) and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based mosaic of Antarctica (MOA) dataset by ~31% (~33.40 km²). Finally, we discussed the practical challenges and future directions in mapping BIRs across Antarctica. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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22 pages, 2978 KiB

Open AccessArticle

Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data

by Barbara Barzycka, Mariusz Grabiec, Jacek Jania, Małgorzata Błaszczyk, Finnur Pálsson, Michał Laska, Dariusz Ignatiuk and Guðfinna Aðalgeirsdóttir

Remote Sens. 2023, 15(3), 690; https://doi.org/10.3390/rs15030690 - 24 Jan 2023

Cited by 2 | Viewed by 2736

Abstract

Changes in glacier zones (e.g., firn, superimposed ice, ice) are good indicators of glacier response to climate change. There are few studies of glacier zone detection by SAR that are focused on more than one ice body and validated by terrestrial data. This study is unique in terms of the dataset collected—four C- and L-band quad-pol satellite SAR images, Ground Penetrating Radar data, shallow glacier cores—and the number of land ice bodies analyzed, namely, three tidewater glaciers in Svalbard and one ice cap in Iceland. The main aim is to assess how well popular methods of SAR analysis perform in distinguishing glacier zones, regardless of factors such as the morphologic differences of the ice bodies, or differences in SAR data. We test and validate three methods of glacier zone detection: (1) Gaussian Mixture Model–Expectation Maximization (GMM-EM) clustering of dual-pol backscattering coefficient (sigma0); (2) GMM-EM of quad-pol Pauli decomposition; and (3) quad-pol H/α Wishart segmentation. The main findings are that the unsupervised classification of both sigma0 and Pauli decomposition are promising methods for distinguishing glacier zones. The former performs better at detecting the firn zone on SAR images, and the latter in the superimposed ice zone. Additionally, C-band SAR data perform better than L-band at detecting firn, but the latter can potentially separate crevasses via the classification of sigma0 or Pauli decomposition. H/α Wishart segmentation resulted in inconsistent results across the tested cases and did not detect crevasses on L-band SAR data. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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26 pages, 7200 KiB

Open AccessArticle

Changes in the Structure of the Snow Cover of Hansbreen (S Spitsbergen) Derived from Repeated High-Frequency Radio-Echo Sounding

by Kamil Kachniarz, Mariusz Grabiec, Dariusz Ignatiuk, Michał Laska and Bartłomiej Luks

Remote Sens. 2023, 15(1), 189; https://doi.org/10.3390/rs15010189 - 29 Dec 2022

Cited by 1 | Viewed by 1379

Abstract

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a “framework” in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE). Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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28 pages, 3339 KiB

Open AccessArticle

Large-Scale Debris Cover Glacier Mapping Using Multisource Object-Based Image Analysis Approach

by Kavita V. Mitkari, Manoj K. Arora, Reet Kamal Tiwari, Sanjeev Sofat, Hemendra S. Gusain and Surya Prakash Tiwari

Remote Sens. 2022, 14(13), 3202; https://doi.org/10.3390/rs14133202 - 4 Jul 2022

Cited by 9 | Viewed by 2952

Abstract

Large-scale debris cover glacier mapping can be efficiently conducted from high spatial resolution (HSR) remote sensing imagery using object-based image analysis (OBIA), which works on a group of pixels. This paper presents the spectral and spatial capabilities of OBIA to classify multiple glacier cover classes using a multisource approach by integrating multispectral, thermal, and slope information into one workflow. The novel contributions of this study are effective mapping of small yet important geomorphological features, classification of shadow regions without manual corrections, discrimination of snow/ice, ice-mixed debris, and supraglacial debris without using shortwave infrared bands, and an adaptation of an area-weighted error matrix specifically built for assessing OBIA’s accuracy. The large-scale glacier cover map is produced with a high overall accuracy of ≈94% (area-weighted error matrix). The proposed OBIA approach also proved to be effective in mapping minor geomorphological features such as small glacial lakes, exposed ice faces, debris cones, rills, and crevasses with individual class accuracies in the range of 96.9–100%. We confirm the portability of our proposed approach by comparing the results with reference glacier inventories and applying it to different sensor data and study areas. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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10 pages, 9698 KiB

Open AccessTechnical Note

Snow Depth Measurements by GNSS-IR at an Automatic Weather Station, NUK-K

by Trine S. Dahl-Jensen, Michele Citterio, Jakob Jakobsen, Andreas P. Ahlstrøm, Kristine M. Larson and Shfaqat A. Khan

Remote Sens. 2022, 14(11), 2563; https://doi.org/10.3390/rs14112563 - 27 May 2022

Cited by 1 | Viewed by 1771

Abstract

Studies have shown that geodetic Global Navigation Satellite System (GNSS) stations can be used to measure snow depths using GNSS interferometric reflectometry (GNSS-IR). Here, we study the results from a customized GNSS setup installed in March through August 2020 at the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station NUK-K located on a small glacier outside Nuuk, Greenland. The setup is not optimized for reflectometry purposes. The site is obstructed between 85 and 215 degrees, and as the power supply is limited due to the remote location, the logging time is limited to 3 h per day. We estimate reflector heights using GNSS-IR and compare the results to a sonic ranger also placed on the weather station. We find that the snow melt measured by GNSS-IR is comparable to the melt measured by the sonic ranger. We expect that a period of up to 45 cm difference between the two is likely related to the much larger footprint GNSS-IR and the topography of the area. The uncertainty on the GNSS-IR reflector heights increase from approximately 2 cm for a snow surface to approximately 5 cm for an ice surface. If reflector height during snow free periods are part of the objective of a similar setup, we suggest increasing the logging time to reduce the uncertainty on the daily estimates. Full article

(This article belongs to the Special Issue Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets)

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