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Remote Sensing of the Cryosphere (Third Edition)
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Remote Sensing of the Cryosphere (Third Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 3017

Special Issue Editors

Prof. Dr. Ulrich Kamp

E-Mail Website
Guest Editor
Earth and Environment Discipline, Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Rd., 114 Science Faculty Center, Dearborn, MI 48128, USA
Interests: cryosphere (glaciers); environmental change (land cover change); environmental hazards (GLOFs, landslides); human-environment interactions (land use change); mountain geography (high mountains, High Asia); paleoenvironmental reconstruction (wetlands); DEMs; UAV; visible remote sensing; repeat photography
Special Issues, Collections and Topics in MDPI journals
Dr. Bijeesh K. Veettil

E-Mail Website
Guest Editor
Laboratory of Ecology and Environmental Management, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City 700000, Vietnam
Interests: environmental assessment and monitoring; remote sensing of the cryosphere; remote sensing of wetlands; Andes; Himalayas
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Dmitry Ganyushkin

E-Mail Website
Guest Editor
Department of Physical Geography and Landscape Design, Saint-Petersburg State University, 199034 St. Petersburg, Russia
Interests: glaciology and glacial geomorphology; geocryology; palaeogeography of mountainous Eurasian countries in Pleistocene and Holocene; rhythms in landscape and space
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the third edition on this topic, “Remote Sensing of the Cryosphere”. The first edition is available at https://www.mdpi.com/journal/remotesensing/special_issues/RS_Cryosphere; the second edition is available at https://www.mdpi.com/journal/remotesensing/special_issues/QK4L3NJ3OS). This third edition, “Remote Sensing of the Cryosphere (Third Edition)”, aims to continue this success.

The cryosphere, the frozen water part of the Earth system, is sensitive to changes in the global climate; hence, scientists monitor its state and changes, particularly with remote sensing. We welcome a broad spectrum of contributions to this Special Issue, including, but not limited to, the following topics:

  • Frozen ground, glacial geomorphology, glaciers, ice caps and sheets, lake/river/sea ice, and snow cover;
  • Recent state of the cryosphere;
  • Changes in the cryosphere, such as deglaciation;
  • Cryospheric hazards and risks;
  • Theories, methodologies, and applications;
  • Laboratory and field investigations;
  • Terrestrial and space measurements;
  • Local, regional, and global scales;
  • Extraterrestrial cryospheres;
  • Any other topic concerned with the cryosphere.

This Special Issue aims to showcase innovative developments in remote sensing research on the cryosphere. Cryospheric science is an interdisciplinary earth science, and we welcome authors from a wide range of disciplines, such as geology, hydrology, meteorology, climatology, biology, engineering, and environmental science.

Prof. Dr. Ulrich Kamp
Dr. Bijeesh K. Veettil
Prof. Dr. Dmitry Ganyushkin
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 250 words) can be sent to the Editorial Office for assessment.

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
  • GIS
  • glacier
  • ice
  • frozen ground
  • remote sensing
  • snow

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Related Special Issues

Published Papers (4 papers)

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Research

24 pages, 23515 KB  
Article
Constraining the Trajectory of Glacier Loss in the Cordillera Real (Bolivia) via a Time-Evolving Inventory
by Giuliana Adrianzen and Andrew G. O. Malone
Remote Sens. 2026, 18(6), 905; https://doi.org/10.3390/rs18060905 - 16 Mar 2026
Viewed by 237
Abstract
Bolivia is home to approximately 20% of the tropical glaciers in South America, which are sensitive indicators of climate change and critical water resources. Glaciers in the Cordillera Real supply meltwater to Bolivia’s administrative capital, La Paz, making it important to accurately assess [...] Read more.
Bolivia is home to approximately 20% of the tropical glaciers in South America, which are sensitive indicators of climate change and critical water resources. Glaciers in the Cordillera Real supply meltwater to Bolivia’s administrative capital, La Paz, making it important to accurately assess their evolution. This study reassesses the trajectory of glacier loss in the Cordillera Real between 1992 and 2024. We construct a time-evolving glacier inventory utilizing remote sensing data (Landsat) and techniques to limit the impact of ephemeral snow cover. Our inventory is at a temporal resolution (5- to 8-year spacing) that allows us to assess the trajectory of glacier loss using statistical models. Between 1992 and 2024, the Cordillera Real lost 103.67 ± 9.97 km2 of glacierized area, representing a 42.0 ± 2.1% reduction. We find that glaciers in the Cordillera Real have been retreating at a constant absolute loss rate of 2.99 [2.32, 3.67] km2 yr−1 and a constant fractional loss rate of 1.6 [1.3, 1.9]% yr−1, contrasting with past studies that suggest accelerating or decelerating loss rates. Our findings provide new insights into the current extent of glaciers in the Cordillera Real and their longevity. The time-evolving inventory is available for use in future studies on the evolution of glaciers in the Cordillera Real and the impacts of their continued loss. Full article
(This article belongs to the Special Issue Remote Sensing of the Cryosphere (Third Edition))
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33 pages, 7256 KB  
Article
Spatiotemporal Variability of Seasonal Snow Cover over 25 Years in the Romanian Carpathians: Insights from a MODIS CGF-Based Approach
by Andrei Ioniță, Iosif Lopătiță, Florina Ardelean, Flavius Sîrbu, Petru Urdea and Alexandru Onaca
Remote Sens. 2026, 18(3), 468; https://doi.org/10.3390/rs18030468 - 2 Feb 2026
Viewed by 518
Abstract
Understanding long-term snow cover dynamics is essential in mountain regions with limited meteorological or in situ observations. This study examines seasonal snow cover evolution across the Romanian Carpathians (2000–2025) using daily MODIS/Terra MOD10A1 Cloud-Gap-Filled data at 500 m resolution. Snow-covered pixels were identified [...] Read more.
Understanding long-term snow cover dynamics is essential in mountain regions with limited meteorological or in situ observations. This study examines seasonal snow cover evolution across the Romanian Carpathians (2000–2025) using daily MODIS/Terra MOD10A1 Cloud-Gap-Filled data at 500 m resolution. Snow-covered pixels were identified using an NDSI ≥ 40 threshold, and snow cover duration (SCD), snow onset date (SOD), and snow end date (SED) were analyzed in relation to elevation and aspect from the FABDEM, complemented by snow-covered area (SCA) and snowline elevation (SLE) metrics. Across the entire range, the snow season shortens mainly due to later onset (+0.28 days/year) and earlier melt (−0.78 days/year), resulting in an SCD decrease of −1.14 days/year. High-elevation (>2000 m) areas show only small changes (SCD: −0.13 days/year; SOD: +0.46 days/year; SED: +0.32 days/year), while the strongest reductions occur at low and mid elevations, where snow persistence is most sensitive to warming; consistent declines in seasonal SCA and a pronounced monthly SLE cycle further document the spatial expression of this variability. Uncertainty was assessed by comparison with station-based snow cover duration (n = 230 station-years), indicating strong agreement (r = 0.95) with a modest negative bias (median: −8 days) and a mean absolute error (MAE) of 16.7 days. Climate correlations highlight air temperature as the dominant covariate of interannual snow-phenology variability, whereas precipitation associations are weaker. Overall, these shifts in snow phenology highlight increasing instability of the Carpathian snow regime and emphasize the value of long-term MODIS observations for tracking cryospheric change in a warming southeastern European mountain system. Full article
(This article belongs to the Special Issue Remote Sensing of the Cryosphere (Third Edition))
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22 pages, 11612 KB  
Article
A Novel Method for Reducing Uncertainty in Subglacial Topography: Implications for Greenland Ice Sheet Volume and Stability
by Oliver T. Bartlett and Steven J. Palmer
Remote Sens. 2026, 18(1), 16; https://doi.org/10.3390/rs18010016 - 20 Dec 2025
Viewed by 644
Abstract
Subglacial topography is a critical boundary condition for ice sheet models projecting past and future ice sheet–climate interactions. Contemporary ice-sheet-wide bed topography datasets are partially derived using mass conservation, but approximately 75% of the most widely used Greenland Ice Sheet (GrIS) dataset is [...] Read more.
Subglacial topography is a critical boundary condition for ice sheet models projecting past and future ice sheet–climate interactions. Contemporary ice-sheet-wide bed topography datasets are partially derived using mass conservation, but approximately 75% of the most widely used Greenland Ice Sheet (GrIS) dataset is based on simple interpolation of airborne radio-echo sounding (RES) measurements, such as kriging or streamline diffusion. Due to limited independent validation data, the errors and biases in this approach are poorly understood, creating largely unknown uncertainties in subglacial topography. Here, we interpolated synthetic RES observations of bed topography over ice-free areas with a known topography at a 5 m spatial resolution and quantify discrepancies. We found that the absolute error in kriged bed topography increases with distance from the input data, though at a reduced rate than previously estimated. The difference between an interpolated elevation estimate and the local mean elevation is a strong predictor of real bed errors (R2 = 0.72), with further improvement as input observation sparsity increases (R2 > 0.82). We propose a method to quantify and reduce uncertainty in kriged bed topography in sparsely surveyed regions, reducing uncertainty for at least 56% of the kriged interior at a 99% confidence interval. Our results suggest that subglacial depth is on average 5 m deeper than previous estimates, though individual areas may be shallower or deeper (σ = 41 m). Consequently, the area grounded below sea level is likely underestimated by 2%, increasing to 29% for regions deeper than 200 m. These findings have potential implications for the future stability of the GrIS under climate change. Full article
(This article belongs to the Special Issue Remote Sensing of the Cryosphere (Third Edition))
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20 pages, 4935 KB  
Article
Spatiotemporal Dynamics of Surface Energy Balance over the Debris-Covered Glacier: A Case Study of Lirung Glacier in the Central Himalaya from 2017 to 2019
by Hehe Liu, Zhen Zhang, Jing Ding and Xue Wang
Remote Sens. 2025, 17(23), 3882; https://doi.org/10.3390/rs17233882 - 29 Nov 2025
Viewed by 674
Abstract
Debris-covered glaciers, with their intricate thermal dynamics and significant spatial heterogeneity, play a pivotal role in elucidating glacier ablation processes and their responses to climate change. However, existing research on their energy balance predominantly focuses on short-term or localized processes, while the long-term [...] Read more.
Debris-covered glaciers, with their intricate thermal dynamics and significant spatial heterogeneity, play a pivotal role in elucidating glacier ablation processes and their responses to climate change. However, existing research on their energy balance predominantly focuses on short-term or localized processes, while the long-term evolution of energy fluxes and the combined effects of debris cover and ice cliffs remain underexplored. This study, focused on the Lirung glacier in the Central Himalaya, leverages multi-source remote sensing data (Landsat 8, MODIS, Planet) in conjunction with meteorological observations and an energy balance model to investigate the spatiotemporal variations in the glacier’s surface energy balance from October 2017 to August 2019. Key findings are as follows: (1) Net radiation flux emerges as the predominant energy driver for ablation, reaching its peak during May–June and substantially outpacing both sensible and latent heat fluxes in magnitude; (2) The energy balance exhibits pronounced spatial heterogeneity, with lower-altitude regions receiving enhanced energy inputs and displaying reduced albedo, thereby magnifying the local ablation flux; (3) The average debris thickness is quantified at 0.55 ± 0.02 m, with thicker debris layers mitigating ablation, while thinner layers exacerbate it; (4) Ice cliffs are characterized by significantly elevated ablation fluxes, with certain areas recording values as high as 1.73 times the glacier-wide mean; (5) The proglacial lake has expanded by 21.1 ± 11.4%, with its temporal variations closely tracking the fluctuations in net radiation flux. These findings provide crucial insights into the energy balance and climate responses of debris-covered glaciers in the Central Himalaya. Full article
(This article belongs to the Special Issue Remote Sensing of the Cryosphere (Third Edition))
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