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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 2023) | Viewed by 20444

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Dr. Sergey V. Popov

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Polar Marine Geosurvey Expedition, Saint Petersburg State University, 198412 St. Petersburg, Russia
Interests: radio-echo sounding; GPR; Antarctic ice sheet; subglacial lakes; subglacial hydrology; mathematical modelling
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Dr. Gang Qiao

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Guest Editor

College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
Interests: antarctica; photogrammetry; remote sensing; satellite altimetry data processing; ice flow velocity; mass balance; evolution analysis of glacier/ice sheet surface microtopography
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Dr. Xiangbin Cui

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Guest Editor

Polar Research Institute of China, Shanghai 200136, China
Interests: radioglaciology; aerogeophysics; subglcial conditions; subglacial hydrological system; ice sheet dynamics; Antarctic ice sheet
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Special Issue Information

Dear Colleagues,

The cryosphere, which includes snow cover, glaciers, ice caps and sheets, sea, lake and river ice, and frozen ground, accounts for a very important fraction of the surface of Earth. This significant part of its surface plays an important role in the functioning of our planet and has thus always been in the focus of wide scientific interest, which is recently even more accentuated due to the crucial role of the cryosphere in the global climate system and its change.

Due to its remoteness, the evaluation of the state of the cryosphere and the understanding of the cryospheric processes would be difficult to imagine these days without remote sensing techniques. Advances in remote sensing techniques constantly expand the possibilities for the effective study of the cryosphere, the importance of which is particularly highlighted by the climate crisis.

We cordially invite you to contribute, by preparing a communication or a full article for this Special Issue dedicated to the cryosphere observations by means of remote sensing. These should refer to your current studies based on using remote sensing techniques and providing new information about the state of the cryosphere and new insights into cryospheric processes, in particular in the context of climate change.

Dr. Sergey V. Popov
Dr. Gang Qiao
Dr. Xiangbin Cui
Guest Editors

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Keywords

radio-echo sounding
GPR
subglacial lakes
satellite altimetry
Arctic
Antarctic
mountain glaciers
permafrost
airborne geophysics
subglacial conditions
satellite and aerial cryosphere
sea ice
snow cover
climate change

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Related Special Issue

The Cryosphere Observations Based on Using Remote Sensing Techniques in Remote Sensing (19 articles)

Published Papers (9 papers)

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Research

30 pages, 9355 KiB

Open AccessArticle

Snow Cover Reconstruction in the Brunswick Peninsula, Patagonia, Derived from a Combination of the Spectral Fusion, Mixture Analysis, and Temporal Interpolation of MODIS Data

by Francisco Aguirre, Deniz Bozkurt, Tobias Sauter, Jorge Carrasco, Christoph Schneider, Ricardo Jaña and Gino Casassa

Remote Sens. 2023, 15(22), 5430; https://doi.org/10.3390/rs15225430 - 20 Nov 2023

Cited by 1 | Viewed by 1428

Abstract

Several methods based on satellite data products are available to estimate snow cover properties, each one with its pros and cons. This work proposes and implements a novel methodology that integrates three main processes applied to MODIS satellite data for snow cover property reconstruction: (1) the increase in the spatial resolution of MODIS (MOD09) data to 250 m using a spectral fusion technique; (2) a new proposal of snow-cloud discrimination; (3) the daily spatio-temporal reconstruction of snow extent and its albedo signature using the endmembers extraction and spectral mixture analyses. The snow cover reconstruction method was applied to the Brunswick Peninsula, Chilean Patagonia, a low-elevation (<1500 m a.s.l.) mid-latitude area. The results show a 98% agreement between MODIS snow detection and ground-based snow measurements at the automatic weather station, Tres Morros (53.3174°S, 71.2790°W), with fractional snow cover values between 20% and 50%, showing a close relationship between snow and vegetation type. The number of snow days compiled from the MODIS data indicates a good performance (Pearson’s correlation of 0.9) compared with the number of skiing days at the Cerro Mirador ski center, Punta Arenas. Although the number of seasonal snow days showed a significant increasing trend of 0.54 days/year in the Brunswick Peninsula during the 2000–2020 period, a significant decrease of −4.64 days/year was detected in 2010–2020. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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26 pages, 9564 KiB

Open AccessArticle

Evaluation and Projection of Precipitation in CMIP6 Models over the Qilian Mountains, China

by Xiaohong Yang, Weijun Sun, Jiake Wu, Jiahang Che, Mengyuan Liu, Qinglin Zhang, Yingshan Wang, Baojuan Huai, Yuzhe Wang and Lei Wang

Remote Sens. 2023, 15(17), 4350; https://doi.org/10.3390/rs15174350 - 4 Sep 2023

Cited by 2 | Viewed by 2615

Abstract

The Qilian Mountains (QMs) act as the “water tower” of the Hexi Corridors, playing an important role in the regional ecosystem security and economic development. Therefore, it is of great significance to understand the spatiotemporal characteristics of precipitation in the QMs. This study evaluated the performance of 21 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) from 1959 to 1988 based on ERA5 and in situ datasets. In addition, the precipitation changing trend from 2015 to 2100 was projected according to four shared socioeconomic pathways (SSPs): namely, SSP126, SSP245, SSP370, and SSP585. The results have shown the following: (1) all CMIP6 models could reflect the same precipitation changing trend, based on the observed datasets (−2.01 mm·10a⁻¹), which was slightly lower than that of ERA5 (2.82 mm·10a⁻¹). Multi-mode ensemble averaging (MME) showed that the projected precipitation-change trend of the four scenarios was 5.73, 9.15, 12.23, and 16.14 mm·10a⁻¹, respectively. (2) The MME and ERA5 showed the same precipitation spatial pattern. Also, during the period 1959–1988, the MME in spring, summer, autumn and winter was 130.07, 224.62, 95.96, and 29.07 mm, respectively, and that of ERA5 was 98.57, 280.77, 96.85, and 22.64 mm, respectively. The largest precipitation difference in summer was because of strong convection and variable circulation. (3) From 2015 to 2100, the snow-to-rain ratio was between 0.1 and 1.1, and the snow-to-rain ratio climate tendency rate was concentrated in the range of −10~0.1 mm·10a⁻¹. Both of these passed the significance test (p < 0.05). The projected rainfall of all four SSPs all showed an increasing trend with values of 6.20, 11.31, 5.64, and 20.41 mm·10a⁻¹, respectively. The snowfall of the four SSPs all showed a decreasing trend with values of 0.42, 2.18, 3.34, and 4.17 mm·10a⁻¹, respectively. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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24 pages, 7144 KiB

Open AccessArticle

Research on the Characteristics of Thermosyphon Embankment Damage and Permafrost Distribution Based on Ground-Penetrating Radar: A Case Study of the Qinghai–Tibet Highway

by Shunshun Qi, Guoyu Li, Dun Chen, Fujun Niu, Zhizhong Sun, Gang Wu, Qingsong Du, Mingtang Chai, Yapeng Cao and Jianwei Yue

Remote Sens. 2023, 15(10), 2651; https://doi.org/10.3390/rs15102651 - 19 May 2023

Cited by 3 | Viewed by 1870

Abstract

In order to research the special embankment (thermosyphon embankment) damages and the distribution of permafrost under the Qinghai–Tibet Highway (QTH) embankment. The section K2952–K2953, which is a typical representative of the QTH, was chosen for the detection and research of the permafrost and embankment damages in order to determine the sources of the damages. In this study, the performance characteristics of the embankment, the active layer, and the permafrost table found in ground-penetrating radar (GPR) images were researched, combined with multi-source. According to the research findings, the construction of the embankment in this section has stabilized the effect on the permafrost table. Under the embankment of the unemployed thermosyphon section, the permafrost distribution has good structural integrity and continuity, with the permafrost table at a depth of around 5 m. The continuity of the permafrost distribution under the embankment in the thermosyphon section was poor, and there was localized degradation, with the permafrost table being approximately 6 m deep. The main cause of the irregular settlement and other damage in this section is the presence of a loose area at the base of the embankment. Although the thermosyphon on both sides of the embankment also plays a role in lifting the permafrost table, it is not ideal for managing the damage to high embankments where the type of permafrost under the embankment is high-temperature permafrost with a high ice content and where the sunny–shady slope effect is obvious. The research results described in this article can therefore provide a crucial foundation for the detection of highway damage and permafrost under embankments in permafrost regions in the future. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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18 pages, 7145 KiB

Open AccessArticle

Delineation Evaluation and Variation of Debris-Covered Glaciers Based on the Multi-Source Remote Sensing Images, Take Glaciers in the Eastern Tomur Peak Region for Example

by Shujing Yang, Feiteng Wang, Yida Xie, Weibo Zhao, Changbin Bai, Jingwen Liu and Chunhai Xu

Remote Sens. 2023, 15(10), 2575; https://doi.org/10.3390/rs15102575 - 15 May 2023

Cited by 5 | Viewed by 1584

Abstract

As a particular type of alpine glacier, debris-covered glaciers are essential for local water resources and glacial disaster warnings. The Eastern Tomur Peak Region (EPTR) is the most concentrated glacier in Tien Shan Mountain, China, where the glaciers have not been studied in detail. This paper evaluates the delineation accuracy of Landsat8 OLI, Sentinel-1A, and GF images for debris-covered glaciers in the EPTR. Each image uses the most advanced delineation method for itself to minimize the error of inherent resolutions. The results show that the accuracy of these images for delineating debris-covered glaciers is very high, and the F1 scores are expressed as 96.73%, 93.55%, and 95.81%, respectively. Therefore, Landsat images were selected to analyze the area change of EPTR from 2000 to 2022 over a 5-year time scale. The results indicate that glaciers of the EPTR decreased by 19.05 km² from 2000 to 2020, accounting for 1.9% (0.08% a⁻¹), and debris increased by 10.8%, which validates the opinion that the presence of debris inhibits glacier melting. The most varied time was 2010–2022, but it was much less than other Tien Shan regions. The lower glacier ablation rate in this area results from the combined effect of decreased bare ice and increased debris. The main reason for the change in debris-covered glaciers is the increase in temperature. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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21 pages, 6657 KiB

Open AccessArticle

Automatic Detection of Subglacial Water Bodies in the AGAP Region, East Antarctica, Based on Short-Time Fourier Transform

by Tong Hao, Liwen Jing, Jiashu Liu, Dailiang Wang, Tiantian Feng, Aiguo Zhao and Rongxing Li

Remote Sens. 2023, 15(2), 363; https://doi.org/10.3390/rs15020363 - 6 Jan 2023

Cited by 7 | Viewed by 3052

Abstract

Subglacial water bodies are critical components in analyzing the instability of the Antarctic ice sheet. Their detection and identification normally rely on geophysical and remote sensing methods such as airborne radar echo sounding (RES), ground seismic, and satellite/airborne altimetry and gravity surveys. In particular, RES surveys are able to detect basal terrain with a relatively high accuracy that can assist with the mapping of subglacial hydrology systems. Traditional RES processing methods for the identification of subglacial water bodies mostly rely on their brightness in radargrams and hydraulic flatness. In this study, we propose an automatic method with the main objective to differentiate the basal materials by quantitatively evaluating the shape of the A-scope waveform near the basal interface in RES radargrams, which has been seldom investigated. We develop an automatic algorithm mainly based on the traditional short-time Fourier transform (STFT) to quantify the shape of the A-scope waveform in radargrams. Specifically, with an appropriate window width applied on the main peak of each A-scope waveform in the RES radargram, STFT shows distinct and contrasting frequency responses at the ice-water interface and ice-rock interface, which is largely dependent upon their different reflection characteristics at the basal interface. We apply this method on 882 RES radargrams collected in the Antarctic’s Gamburtsev Province (AGAP) in East Antarctica. There are 8822 identified A-scopes with the calculated detection value larger than the set threshold, out of the overall 1,515,065 valid A-scopes in these 882 RES radargrams. Although these identified A-scopes only takes 0.58% of the overall A-scope population, they show exceptionally continuous distribution to represent the subglacial water bodies. Through a comprehensive comparison with existing inventories of subglacial lakes, we successfully verify the validity and advantages of our method in identifying subglacial water bodies using the detection probability for other basal materials of theoretically the highest along-track resolution. The frequency signature obtained by the proposed joint time–frequency analysis provides a new corridor of investigation that can be further expanded to multivariable deep learning approaches for subglacial and englacial material characterization, as well as subglacial hydrology mapping. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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20 pages, 19444 KiB

Open AccessArticle

Tectonic Implications for the Gamburtsev Subglacial Mountains, East Antarctica, from Airborne Gravity and Magnetic Data

by Guochao Wu, Fausto Ferraccioli, Wenna Zhou, Yuan Yuan, Jinyao Gao and Gang Tian

Remote Sens. 2023, 15(2), 306; https://doi.org/10.3390/rs15020306 - 4 Jan 2023

Cited by 3 | Viewed by 2244

Abstract

The Gamburtsev Subglacial Mountains (GSMs) in the interior East Antarctic Craton are entirely buried under the massive East Antarctic ice sheet, with a ~50–60 km thick crust and ~200 km thick lithosphere, but little is known of the crustal structure and uplift mechanism. Here, we use airborne gravity and aeromagnetic anomalies for characteristic analysis and inverse calculations. The gravity and magnetic images show three distinct geophysical domains. Based on the gravity anomalies, a dense lower crustal root is modelled to underlie the GSMs, which may have formed by underplating during the continental collision of Antarctica and India. The high frequency linear magnetic characteristics parallel to the suture zone suggest that the upper crustal architecture is dominated by thrusts, consisting of a large transpressional fault system with a trailing contractional imbricate fan. A 2D model along the seismic profile is created to investigate the crustal architecture of the GSMs with the aid of depth to magnetic source estimates. Combined with the calculated crustal geometry and physical properties and the geological background of East Antarctica, a new evolutionary model is proposed, suggesting that the GSMs are underlain by part of a Pan-African age advancing accretionary orogen superimposed on Precambrian basement. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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18 pages, 3895 KiB

Open AccessArticle

Dynamic Monitoring of Debris-Covered Glacier Surface Velocity and Ice Thickness of Mt.Tomur, Tian Shan, China

by Changbin Bai, Feiteng Wang, Lin Wang, Chunhai Xu, Xiaoying Yue, Shujing Yang, Puyu Wang, Yanqun Bi and Haining Wei

Remote Sens. 2023, 15(1), 150; https://doi.org/10.3390/rs15010150 - 27 Dec 2022

Cited by 7 | Viewed by 2156

Abstract

The Mt.Tomur glaciers, in the Tian Shan mountains of Western China, are usually debris-covered, and due to climate change, glacial hazards are becoming more frequent in this region. However, no changes in the long-time series of glacier surface velocities have been observed in this region. Conducting field measurements in high-altitude mountains is relatively difficult, and consequently, the dynamics and driving factors are less studied. Here, image-correlation offset tracking using Landsat images was exploited to estimate the glacier surface velocity of glaciers in the Mt.Tomur region from 2000 to 2020 and to assess glacier ice thickness. The results show that the glacier surface velocity in the Mt.Tomur region showed a significant slowdown during 2000–2020, from 6.71 ± 0.66 m a⁻¹ to 3.95 ± 0.66 m a⁻¹, an overall decrease of 41.13%. The maximum glacier ice thickness in the Mt.Tomur region was estimated based on the ice flow principle being 171.27 ± 17.10 m, and the glacier average thickness is 50.00 ± 5.0 m. Glacier thickness at first increases with increasing altitude, showing more than 100 ± 10 m ice thickness between 3400 m and 4300 m, and then decreases with further increases in altitude. The reliability of the surface velocity and ice thickness obtained from remote sensing was proved using the measured surface velocity and ice thickness of Qingbingtan glacier No. 72 stall (the correlation coefficient R² > 0.85). The debris cover has an overall mitigating effect on the ablation and movement rate of Qingbingtan Glacier No. 72; however, it has an accelerating effect on the ablation and movement rate of glacier No. 74. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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17 pages, 5154 KiB

Open AccessArticle

Surface Albedo and Snowline Altitude Estimation Using Optical Satellite Imagery and In Situ Measurements in Muz Taw Glacier, Sawir Mountains

by Fengchen Yu, Puyu Wang and Hongliang Li

Remote Sens. 2022, 14(24), 6405; https://doi.org/10.3390/rs14246405 - 19 Dec 2022

Cited by 3 | Viewed by 2239

Abstract

Glacier surface albedo strongly affects glacier mass balance by controlling the glacier surface energy budget. As an indicator of the equilibrium line altitude (ELA), the glacier snowline altitude (SLA) at the end of the melt season can reflect variations in the glacier mass balance. Therefore, it is extremely crucial to investigate the changes of glacier surface albedo and glacier SLA for calculating and evaluating glacier mass loss. In this study, from 2011 to 2021, the surface albedo of the Muz Taw Glacier was derived from Landsat images with a spatial resolution of 30 m and from the Moderate Resolution Imaging Spectroradiometer albedo products (MOD10A1) with a temporal resolution of 1 day, which was verified through the albedo measured by the Automatic Weather Station (AWS) installed in the glacier. Moreover, the glacier SLA was determined based on the variation in the surface albedo, with the altitude change along the glacier main flowline derived from the Landsat image at the end of the melt season. The correlation coefficient of >0.7, with a risk of error lower than 5%, between the surface albedo retrieved from remote sensing images and the in situ measurement data indicated that the method of deriving the glacier surface albedo by the remote sensing method was reliable. The annual average albedo showed a slight upward trend (0.24%) from 2011 to 2021. A unimodal seasonal variation in albedo was demonstrated, with the downward trend from January to August and the upward trend from August to December. The spatial distribution of the albedo was not entirely dependent on altitude due to the dramatic effects of the topography and glacier surface conditions. The average SLA was 3446 m a.s.l., with a variation of 160 m from 2011 to 2021. The correlation analysis between the glacier SLA and annual mean temperature/annual precipitation demonstrated that the variations of the average SLA on the Muz Taw Glacier was primarily affected by the air temperature. This study improved our understanding of the ablation process and mechanism of the Muz Taw Glacier. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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15 pages, 4976 KiB

Open AccessArticle

Increased Mass Loss of Glaciers in the Sawir Mountains of Central Asia between 1959 and 2021

by Changbin Bai, Feiteng Wang, Yanqun Bi, Lin Wang, Chunhai Xu, Xiaoying Yue, Shujing Yang and Puyu Wang

Remote Sens. 2022, 14(21), 5406; https://doi.org/10.3390/rs14215406 - 28 Oct 2022

Cited by 5 | Viewed by 1852

Abstract

Glacier mass balance can be regarded as a major direct index of climate variations. In this paper, a geodetic method was used to evaluate the mass balance of Sawir glaciers based on topographic map DEM (Digital Elevation Model), SRTM 30 m DEM, ASTER 30 m DEM, and Sentinel-1 Synthetic Aperture Radar 10 m DEM between 1959–2021, in order to explore the response to climatic alterations. In the case of Muz Taw glacier, the first comprehensive dataset concerning mass-balance readings for the 2014–2021 period was provided based on the eight-year consecutive field measurements. The glaciological average mass balance reached –883.4 ± 130 mm a^–1 during this period. The geodetic mass balance for all glaciers of the Sawir Mountain range was −0.43 ± 0.12 m w. e. a⁻¹ between 1959 and 2000, and accelerated to −0.56 ± 0.13 m w. e. a⁻¹ between 2000 and 2021. A comparison of field measurements and remote-sensing approaches for determining the Muz Taw glacier’s mass balance between 2014–2021 proves the feasibility of the remote-sensing approach, which involves mass-balance monitoring based on DEMdata. In addition, our findings support the contention that air temperature is the dominant factor for accelerated glacier mass loss and surface elevation change. Full article

(This article belongs to the Special Issue The Cryosphere Observations Based on Using Remote Sensing Techniques II)

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