Advances in Cryosphere Monitoring: Integrating Multi-Source Remote Sensing and AI Technologies

Dear Colleagues,

This Special Issue addresses the critical challenges of monitoring glaciers, snow cover, and permafrost dynamics within the cryosphere through cutting-edge remote sensing technologies and artificial intelligence (AI)-driven methodologies. As a vital component of the Earth's climate system, the cryosphere is undergoing an accelerated transformation due to climate change, necessitating advanced observational frameworks for quantifying its spatiotemporal variability.

Remote sensing provides a scalable, non-invasive platform to assess key cryospheric parameters, including  the glacier mass balance, ice flow velocity, snow water equivalent (SWE), and permafrost thermal state. Satellite-based optical, radar, and thermal infrared sensors enable the systematic tracking of glacier retreat patterns, while hyperspectral imaging and synthetic aperture radar (SAR) enhance the characterization of snowpack properties and subsurface permafrost degradation. Complementing spaceborne observations, unmanned aerial vehicles (UAVs) offer high-resolution monitoring of localized cryospheric processes, bridging the gap between field measurements and satellite data.

Emerging innovations in multi-sensor data fusion and AI algorithms (e.g., deep learning and computer vision) are revolutionizing cryosphere monitoring. Machine learning models trained on multi-temporal satellite datasets improve cryosphere change predictions. The integration of multi-source remote sensing data (e.g., passive/active sensors and LiDAR) with physics-informed AI frameworks enables the robust quantification of cryosphere–climate feedback mechanisms.

This Special Issue aims to showcase the latest advancements in remote sensing and AI applications for cryosphere monitoring. By focusing on glaciers, snow, and permafrost, we seek to highlight novel research that addresses critical gaps in our understanding of cryosphere dynamics. These studies contribute to a comprehensive understanding of cryosphere dynamics, enabling better predictions of climate-related changes and their far-reaching consequences for the environment and humans.

This Special Issue will cover (but will not be limited to) the following topics:

1. Glacier Dynamics and Mass Balance.

   - Remote sensing techniques for monitoring glacier retreat, advance, and mass balance.

   - The use of SAR (Synthetic Aperture Radar), LiDAR, and optical imagery for glacier monitoring.

   - The impacts of climate change on glacier dynamics.

2. Snow Cover and Snow Water Equivalent (SWE).

   - Remote sensing of seasonal snow cover extent and variability.

   - The estimation of snow water equivalent using passive microwave, optical, and radar data.

   - Snow albedo feedback and its role in climate systems.

3. Permafrost Monitoring and Thaw.

   - Remote sensing of permafrost distribution.

   - The use of thermal infrared, InSAR, and ground-penetrating radar for permafrost studies.

   - The impacts of permafrost thaw on ecosystems and infrastructure.

4. Cryosphere–Climate Interactions.

   - Feedback mechanisms between cryosphere changes and the global climate.

   - The role of cryospheric components in the Earth’s energy balance.

   - Remote sensing of cryosphere–atmosphere interactions.

5. Cryosphere Disasters.

   - Glacial hazards, snow-related hazards, and permafrost-related hazards.

   - Integrated cryosphere disaster risk management.

   - Socioeconomic and ecological impacts.

6. Emerging Technologies and Methods.

   - Advances in remote sensing technologies (e.g., hyperspectral imaging, UAVs, AI applications).

   - The integration of multi-sensor data for cryosphere monitoring.

   - Challenges and opportunities in remote sensing of the cryosphere.

7. Impacts on Ecosystems and Human Systems.

   - The effects of glacier retreat and snow cover changes on water resources.

   - Permafrost thaw and its impact on carbon release and infrastructure.

   - The socioeconomic implications of cryosphere changes. 

Prof. Dr. Puyu Wang
Prof. Dr. Ze Zhang
Prof. Dr. Xuejiao Wu
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.

• cryosphere
• remote sensing
• AI technology
• glacier monitoring
• snow cover
• permafrost observation
• climate change impacts