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Advances in Remote Sensing of the Polar Ice with High Frequency (HF) to L-Band Radar

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

Deadline for manuscript submissions: 31 January 2026 | Viewed by 493

Special Issue Editors


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Guest Editor
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Interests: radioglaciology; radio-echo sounding; GPR; Antarctic ice sheet; subglcial conditions

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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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Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
Interests: system development of radar sounding; digital system design, and signal processing

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Guest Editor
Centre Tecnologic De Telecomunicacions De Catalunya, Barcelona, Spain
Interests: snow water equivalent; radars; remote sensing; GNSS; cryosphere
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ice sounding radar is the main technical means for detecting polar ice and snow media. It provides important basic observational data for studying geometric characteristics, internal structures, subglacial topography and environment of polar ice and snow. In the 1950s, humans first discovered that electromagnetic waves in specific frequency bands could “penetrate” the Antarctic ice sheet; in the 1960s, we developed an ice sounding radar system for the detection of polar ice sheets under ice. Over the recent 60 years, with the development of computers, electronic information, and satellite positioning and navigation technology, the research on ice sounding radar technology has rapidly developed, resulting in a diversified ice sounding radar system suitable for the different detection requirements of polar ice sheets, sea ice and snow covers. 

This Special Issue welcomes studies covering various factettes of L-band ice sounding radars with a high frequency. Topics may cover the design of different kinds of ice sounding radar systems, signal processing methods used to improve the performance of ice sounding radar systems (including detection depth, cross-track resolution, and vertical resolution), and research on the observation of polar ice sheets, sea ice, and snow covers via ice sounding radar. Articles may address, but are not limited, to the following topics:

  • Ice sounding radar design.
  • Detection depth improvement.
  • Vertical resolution improvement.
  • Along-track resolution improvement.
  • Cross-track resolution improvement.
  • New platforms for ice sounding radars.
  • New observations made using ice sounding radars.

Dr. Shinan Lang
Dr. Xiangbin Cui
Dr. Bo Zhao
Dr. Pedro Fidel Espín-López
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 sounding radar
  • system design
  • signal processing
  • Antarctic
  • Arctic
  • mountain glaciers
  • subglacial conditions
  • snow cover
  • sea ice
  • satellite and aerial cryosphere

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Published Papers (1 paper)

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Research

21 pages, 6547 KB  
Article
A High-Resolution Sea Ice Concentration Retrieval from Ice-WaterNet Using Sentinel-1 SAR Imagery in Fram Strait, Arctic
by Tingting Zhu, Xiangbin Cui and Yu Zhang
Remote Sens. 2025, 17(20), 3475; https://doi.org/10.3390/rs17203475 - 17 Oct 2025
Viewed by 292
Abstract
High spatial resolution sea ice concentration (SIC) is crucial for global climate and marine activity. However, retrieving high spatial resolution SIC from passive microwave sensors is challenging due to the trade-off between spatial resolution and atmospheric contamination. Our study develops the Ice-WaterNet framework, [...] Read more.
High spatial resolution sea ice concentration (SIC) is crucial for global climate and marine activity. However, retrieving high spatial resolution SIC from passive microwave sensors is challenging due to the trade-off between spatial resolution and atmospheric contamination. Our study develops the Ice-WaterNet framework, a novel superpixel-based deep learning model that integrates Conditional Random Fields (CRF) with a dual-attention U-Net to enhance ice–water classification in Synthetic Aperture Radar (SAR) imagery. The Ice-WaterNet model has been extensively tested on 2735 Sentinel-1 dual-polarized SAR images from 2021 to 2023, covering both winter and summer seasons in the Fram Strait. To tackle the complex surface features during the melt season, wind-roughened open water, and varying ice floe sizes, a superpixel strategy is employed to efficiently reduce classification uncertainty. Uncertain superpixels identified by CRF are iteratively refined using the U-Net attention mechanism. Experimental results demonstrate that Ice-WaterNet achieves significant improvements in classification accuracy, outperforming CRF and U-Net by 3.375% in Intersection over Union (IoU) and 3.09% in F1-score during the melt season, and by 1.96 in IoU and 1.75 in F1-score during the freeze season. The derived high-resolution SIC products, updated every two days, were evaluated against Met Norway ice charts and compared with ASI from AMSR-2 and SSM/I, showing a substantial reduction in misclassification in marginal ice zones, particularly under melting conditions. These findings underscore the potential of Ice-WaterNet in supporting precise sea ice monitoring and climate change research. Full article
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