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Advances in Remote Sensing in Glacial and Periglacial Geomorphology

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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 2024) | Viewed by 17312

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Special Issue Editors

Prof. Dr. José Juan de Sanjosé Blasco

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Guest Editor

Department of Graphic Expression, Polytechnic School, University of Extremadura, 10003 Cáceres, Spain
Interests: geodesy; cartography; photogrammetry; cultural heritage; glacier movement; coastal regression
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Dr. Manuel Gómez Lende

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Department of Geography, Urban and Regional Planning, Universidad de Cantabria, 39005 Santander, Spain
Interests: geomorphology; ice caves; glacial and periglacial processes and morphologies; mountain environments; cartography and mapping; coastal geomorphology
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Prof. Dr. Enrique Serrano Cañadas

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Guest Editor

Department of Geography, University of Valladolid, 47011 Valladolid, Spain
Interests: geomorphology; glacial and periglacial processes; mountain environments; mapping
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Processes related to cold environments are very dynamic and are changing rapidly under the influence of climate and global changes. The systematic and precise control of processes involved in the disappearance of ice in the cryosphere, the glacial and periglacial processes and the degradation of permafrost is needed. They are also important to know in order to determine the magnitude of these changes' consequences, such as on hydrology, vegetation, ecosystems and landscapes, or their potential risks. Remote sensing allows for these processes to be effectively controlled in different environments, and a wide variety of techniques—InSar, LIDAR, TLS, GPS-RTK, SfM—enable their active tracking and monitoring. Recent technological advances and their applications in different environments are contributions of the first order both to the advancement of knowledge of earth surface dynamics and the varying responses to anthropogenic changes.

Aim of the Special Issue and how the subject relates to the journal scope.
This Special Issue focuses on contributions to the knowledge of changes in the cryosphere through the application of remote sensing. The main aim is the application of remote sensing to the retreat and disappearance of glaciers; the dynamics, velocity and volume changes in rock glaciers and ice caves; the changes in processes related to permafrost; and the degradation of ice in the cryosphere in any modality. These processes are analysed using varies techniques of remote sensing, applied individually or combined, to learn the behaviour of ice on Earth.

This focus fits the aim of the journal as a monograph focused on applied studies of the cryosphere by means of multi-spectral and hyperspectral remote sensing; lidar and laser scanning; geometric reconstruction; change detection; image processing and pattern recognition; operational processing facilities; spaceborne, airborne and terrestrial platforms; and remote sensing applications.

Suggested themes and article types for submissions.

Themes:

Glacier retreat in mountain and polar environments;
Demise of small glaciers;
Rock glacier inventory;
Rock glacier kinematic;
Rock glacier velocity;
Permafrost related processes;
Ice caves inventory;
Ice caves mass balances;
InSAR techniques;
Digital Photogrammetry Techniques;
UAV surveys;
Geodetic Mass Balances;
TLS techniques.

Types:
Reviews, cases and research articles.

Prof. Dr. José Juan de Sanjosé Blasco
Dr. Manuel Gómez Lende
Prof. Dr. Enrique Serrano Cañadas
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

cryosphere
glaciers
rock glaciers
ice caves
permafrost degradation
remote sensing techniques

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Related Special Issue

Advances in Remote Sensing in Glacial and Periglacial Geomorphology (Second Edition) in Remote Sensing

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Research

22 pages, 16146 KiB

Open AccessArticle

The Impact of Glacial Shrinkage on Future Streamflow in the Urumqi River Source Region of Eastern Tien Shan, Central Asia

by Weibo Zhao, Zhongqin Li, Hongliang Li, Chunhai Xu, Jianxin Mu and Yefei Yang

Remote Sens. 2024, 16(14), 2546; https://doi.org/10.3390/rs16142546 - 11 Jul 2024

Viewed by 1220

Abstract

Understanding changes in runoff due to climate variations in glacier-dominated headwaters is key to managing water resources and dryland watersheds effectively and rationally. The continuous glacier shrinkage caused by climate warming has significantly impacted the water supply and ecological systems in the vast arid regions of Central Asia, attracting extensive public concern. The study results indicate an increase in total runoff at the Urumqi River source region during both the baseline (1997–2016) and mid-century (2040–2059) periods, encompassing rain, glacier meltwater, and snowmelt components. Compared to the baseline period, the temperature increases by the mid-century under the three climate scenarios (SSP1−26, SSP2−45, and SSP5−85) range from 0.98 to 1.48 °C. In this region, during the period from 1997 to 2016, glacier meltwater was the dominant component of runoff, comprising 42.10–43.79% of the total, followed by snowmelt at 29.64–30.40% and rainfall contributions of 26.56–27.49%. Additionally, glacier storage in this typical catchment responds quickly to temperature fluctuations, significantly impacting runoff. The Urumqi River source region’s runoff exhibits heightened sensitivity to these temperature shifts compared to precipitation effects. We hypothesized three glacier coverage scenarios: unchanged at 100% glaciation, reduced by half to 50%, and fully retreated to 0% glaciation. Analysis of these scenarios demonstrated that glaciers are pivotal in runoff formation. Under the SSP1−26, SSP2−45, and SSP5−85 climate scenarios, glaciers contributed additional runoff increases of 51.61%, 57.64%, and 62.07%, respectively. Generally, glaciers play a critical role in supplying water in dry areas. Thus, accurately forecasting future water resource shifts in high-altitude glacier regions is crucial for downstream water resource management and utilization. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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21 pages, 4350 KiB

Open AccessFeature PaperArticle

A Comparison of Satellite Imagery Sources for Automated Detection of Retrogressive Thaw Slumps

by Heidi Rodenhizer, Yili Yang, Greg Fiske, Stefano Potter, Tiffany Windholz, Andrew Mullen, Jennifer D. Watts and Brendan M. Rogers

Remote Sens. 2024, 16(13), 2361; https://doi.org/10.3390/rs16132361 - 27 Jun 2024

Cited by 4 | Viewed by 1817

Abstract

Retrogressive thaw slumps (RTS) are a form of abrupt permafrost thaw that can rapidly mobilize ancient frozen soil carbon, magnifying the permafrost carbon feedback. However, the magnitude of this effect is uncertain, largely due to limited information about the distribution and extent of RTS across the circumpolar region. Although deep learning methods such as Convolutional Neural Networks (CNN) have shown the ability to map RTS from high-resolution satellite imagery (≤10 m), challenges remain in deploying these models across large areas. Imagery selection and procurement remain one of the largest challenges to upscaling RTS mapping projects, as the user must balance cost with resolution and sensor quality. In this study, we compared the performance of three satellite imagery sources that differed in terms of sensor quality and cost in predicting RTS using a Unet3+ CNN model and identified RTS characteristics that impact detectability. Maxar WorldView imagery was the most expensive option, with a ground sample distance of 1.85 m in the multispectral bands (downloaded at 4 m resolution). Planet Labs PlanetScope imagery was a less expensive option with a ground sample distance of approximately 3.0–4.2 m (downloaded at 3 m resolution). Although PlanetScope imagery was downloaded at a higher resolution than WorldView, the radiometric footprint is around 10–12 m, resulting in less crisp imagery. Finally, Sentinel-2 imagery is freely available and has a 10 m resolution. We used 756 RTS polygons from seven sites across Arctic Canada and Siberia in model training and 63 RTS polygons in model testing. The mean IoU of the validation and testing data sets were 0.69 and 0.75 for the WorldView model, 0.70 and 0.71 for the PlanetScope model, and 0.66 and 0.68 for the Sentinel-2 model, respectively. The IoU of the RTS class was nonlinearly related to the RTS Area, showing a strong positive correlation that attenuated as the RTS Area increased. The models were better able to predict RTS that appeared bright on a dark background and were less able to predict RTS that had higher plant cover, indicating that bare ground was a primary way the models detected RTS. Additionally, the models performed less well in wet areas or areas with patchy ground cover. These results indicate that all imagery sources tested here were able to predict larger RTS, but higher-quality imagery allows more accurate detection of smaller RTS. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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17 pages, 3860 KiB

Open AccessArticle

Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection

by Hao Ye, Guowang Jin, Hongmin Zhang, Xin Xiong, Jiahao Li and Jiajun Wang

Remote Sens. 2024, 16(3), 546; https://doi.org/10.3390/rs16030546 - 31 Jan 2024

Cited by 2 | Viewed by 1649

Abstract

Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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13 pages, 37053 KiB

Open AccessCommunication

Multiple Close-Range Geomatic Techniques for the Kinematic Study of the La Paúl Rock Glacier, Southern Pyrenees

by Adrián Martínez-Fernández, Enrique Serrano, José Juan de Sanjosé Blasco, Manuel Gómez-Lende, Manuel Sánchez-Fernández, Alfonso Pisabarro and Alan Atkinson

Remote Sens. 2024, 16(1), 134; https://doi.org/10.3390/rs16010134 - 28 Dec 2023

Viewed by 1836

Abstract

Rock glaciers are one of the most representative elements of mountain permafrost. Their study can contribute to modelling climate change and its effect on natural and anthropogenic environments. Therefore, it is crucial to understand the evolution and quantify the changes in these periglacial landforms at a global level. This study aims to present the monitoring work carried out on the Pyrenean rock glacier of La Paúl (42°39′40″N, 0°26′34″E) from 2013 to 2020, employing in situ geomatics techniques to determine the landform surface kinematics accurately. For this purpose, global navigation satellite systems (GNSS), terrestrial laser scanners (TLS), and unmanned aerial vehicles (UAV) photogrammetry techniques were used simultaneously to evaluate their compatibility in quantifying displacements. Based on 2D and 3D analyses, the results demonstrate the high surface activity of the rock glacier, with mean variations reaching 36 cm/year (GNSS) and a distribution of deformations that, although intensified on its western side, are present on the entire surface of La Paúl. This study uses state-of-the-art geomatics techniques to present dependable and updated quantitative data on a periglacial landform’s recent development in under-researched areas, such as the Pyrenean temperate high mountain. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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19 pages, 14718 KiB

Open AccessArticle

The Variability of Snow Cover and Its Contribution to Water Resources in the Chinese Altai Mountains from 2000 to 2022

by Fengchen Yu, Puyu Wang, Lin Liu, Hongliang Li and Zhengyong Zhang

Remote Sens. 2023, 15(24), 5765; https://doi.org/10.3390/rs15245765 - 17 Dec 2023

Cited by 1 | Viewed by 1605

Abstract

As one of the major water supply systems for inland rivers, especially in arid and semi-arid regions, snow cover strongly affects hydrological cycles. In this study, remote sensing datasets combined with in-situ observation data from a route survey of snow cover were used to investigate the changes in snow cover parameters on the Chinese Altai Mountains from 2000 to 2022, and the responses of snow cover to climate and hydrology were also discussed. The annual snow cover frequency (SCF), snow cover area, snow depth (SD), and snow density were 45.03%, 2.27 × 10⁴ km², 23.4 cm, and ~0.21 g·cm⁻³, respectively. The snow water equivalent ranged from 0.58 km³ to 1.49 km³, with an average of 1.12 km³. Higher and lower SCF were mainly distributed at high elevations and on both sides of the Irtysh river. The maximum and minimum snow cover parameters occurred in the Burqin River Basin and the Lhaster River Basin. In years with high SCF, abnormal westerly airflow was favorable for water vapor transport to the Chinese Altai Mountains, resulting in strong snowfall, and vice versa in years with low SCF. There were significant seasonal differences in the impact of temperature and precipitation on regional SCF changes. The snowmelt runoff ratios were 11.2%, 25.30%, 8.04%, 30.22%, and 11.56% in the Irtysh, Kayit, Haba, Kelan, and Burqin River Basins. Snow meltwater has made a significant contribution to the hydrology of the Chinese Altai Mountains. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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18 pages, 27374 KiB

Open AccessArticle

Cross-Polarized SfM Photogrammetry for the Spatial Reconstruction of Challenging Surfaces, the Case Study of Dobšiná Ice Cave (Slovakia)

by Karol Bartoš, Katarína Pukanská, Ľubomír Kseňak, Juraj Gašinec and Pavel Bella

Remote Sens. 2023, 15(18), 4481; https://doi.org/10.3390/rs15184481 - 12 Sep 2023

Cited by 6 | Viewed by 2292

Abstract

Geodetic methods are integral to mapping surface and subsurface objects and phenomena. Modern geodetic technologies such as laser scanning and digital photogrammetry have also become a standard part of the mapping and documentation of cave spaces. In some cases, these technologies cannot accurately capture the measured surface and thus provide reliable data. One such example is the ice with specific surface characteristics in caves with ice deposits. One of the world’s most studied ice caves is the Dobšiná Ice Cave (Slovakia), which has undergone significant changes in the ice-filling area and volume in recent years. To monitor and analyze all these changes properly, we need to know the surface and volume of this ice mass and monitor it regularly. Where modern geodetic methods such as terrestrial laser scanning (TLS) or digital photogrammetry may fail due to the ice’s physical properties, we propose using cross-polarized Structure-from-Motion (SfM) photogrammetry. As a case study, this method was used in a 28 m long ice tunnel in this cave. Two polarizing filters (on the flash as a light source and on the camera lens) were used in 90° rotation to each other to achieve the cross-polarization effect and remove surface reflections. This removed the surface reflections, giving us a compact and accurate point cloud of the entire tunnel. The dense cloud from cross-polarized (CP) photogrammetry is denser and more compact and does not contain as many outliers and noise points when compared to non-cross-polarized (non-CP) photogrammetry. The TLS point cloud covers the entire surface of the tunnel without significant holes; however, the penetration of the beam through the ice makes such a cloud unusable. Only the cloud from CP photogrammetry covers the entire surface of the tunnel densely enough without additional noise. This methodology can then be used in other parts of the cave or other geomorphological applications to suppress reflections so high-quality results for further processing and analysis can be obtained. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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27 pages, 76300 KiB

Open AccessArticle

Deciphering Small-Scale Seasonal Surface Dynamics of Rock Glaciers in the Central European Alps Using DInSAR Time Series

by Sebastian Buchelt, Jan Henrik Blöthe, Claudia Kuenzer, Andreas Schmitt, Tobias Ullmann, Marius Philipp and Christof Kneisel

Remote Sens. 2023, 15(12), 2982; https://doi.org/10.3390/rs15122982 - 7 Jun 2023

Cited by 6 | Viewed by 2381

Abstract

The Essential Climate Variable (ECV) Permafrost is currently undergoing strong changes due to rising ground and air temperatures. Surface movement, forming characteristic landforms such as rock glaciers, is one key indicator for mountain permafrost. Monitoring this movement can indicate ongoing changes in permafrost; therefore, rock glacier velocity (RGV) has recently been added as an ECV product. Despite the increased understanding of rock glacier dynamics in recent years, most observations are either limited in terms of the spatial coverage or temporal resolution. According to recent studies, Sentinel-1 (C-band) Differential SAR Interferometry (DInSAR) has potential for monitoring RGVs at high spatial and temporal resolutions. However, the suitability of DInSAR for the detection of heterogeneous small-scale spatial patterns of rock glacier velocities was never at the center of these studies. We address this shortcoming by generating and analyzing Sentinel-1 DInSAR time series over five years to detect small-scale displacement patterns of five high alpine permafrost environments located in the Central European Alps on a weekly basis at a range of a few millimeters. Our approach is based on a semi-automated procedure using open-source programs (SNAP, pyrate) and provides East-West displacement and elevation change with a ground sampling distance of 5 m. Comparison with annual movement derived from orthophotos and unpiloted aerial vehicle (UAV) data shows that DInSAR covers about one third of the total movement, which represents the proportion of the year suited for DInSAR, and shows good spatial agreement (Pearson R: 0.42–0.74, RMSE: 4.7–11.6 cm/a) except for areas with phase unwrapping errors. Moreover, the DInSAR time series unveils spatio-temporal variations and distinct seasonal movement dynamics related to different drivers and processes as well as internal structures. Combining our approach with in situ observations could help to achieve a more holistic understanding of rock glacier dynamics and to assess the future evolution of permafrost under changing climatic conditions. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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17 pages, 13401 KiB

Open AccessArticle

Glaciogenic Periglacial Landform in the Making—Geomorphological Evolution of a Rockfall on a Small Glacier in the Horlachtal, Stubai Alps, Austria

by Fabian Fleischer, Florian Haas, Moritz Altmann, Jakob Rom, Camillo Ressl and Michael Becht

Remote Sens. 2023, 15(6), 1472; https://doi.org/10.3390/rs15061472 - 7 Mar 2023

Cited by 4 | Viewed by 2825

Abstract

Deglaciation in high mountain areas signifies the transition from glacial to periglacial conditioned landscapes. Due to the reduced melt rate of debris-covered glacier ice, these areas of the glacier may persist long after the surrounding glacier has melted, resulting in the formation of distinct post-glacial landforms. In this study, we examine the geomorphological evolution and potential future development of a 19,267 m³ ± 204 m³ rockfall from the permafrost-affected headwall on the low-elevated Zwieselbachferner in the Horlachtal, Stubai Alps, Austria. The analysis uses multi-epochal remote sensing data, including photogrammetrically and airborne laser scanning-derived digital elevation models, orthophotos, and satellite data, covering a period from the initial rockfall in 2003/2004 to 2022. The data reveals that the rockfall event resulted in the formation of a supraglacial debris layer of varying thickness, spanning an area of 15,920 m². Subsequently, 13 further rockfalls ranging from 67 m³ ± 6 m³ to 4250 m³ ± 121 m³ were detected. The mean ice thickness of the debris-covered area only slightly decreased between 2006 and 2022, in contrast to the surrounding glacier, whose thickness and length have strongly decreased. This results in the formation of a steep front and flanks that become increasingly covered by debris redistribution. The study suggests that the glacier ice covered by rockfall-derived debris will remain as a periglacial landform of glacial origin after the complete melting of the surrounding glacier. Full article

(This article belongs to the Special Issue Advances in Remote Sensing in Glacial and Periglacial Geomorphology)

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