Xie et al. (2026) Sea Ice Concentration Retrieval in the Arctic and Antarctic Using FY-3E GNSS-R Data

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-01-15
• Authors: Tingyu Xie, Cong Yin, Weihua Bai, Di Song, Feixiong Huang, Junming Xia, Xiaochun Zhai, Yueqiang Sun, Qifei Du, Bin Wang
• DOI: 10.3390/rs18020285

Research Groups

Chinese meteorological/space agencies involved in the Fengyun-3E satellite program and its data utilization.

Short Summary

This study presents the first comprehensive investigation of China’s Fengyun-3E GNOS-II GNSS-R for bipolar Sea Ice Concentration (SIC) retrieval, demonstrating its feasibility and high accuracy with strong agreement to reference data across both polar regions.

Objective

• To conduct the first comprehensive investigation of China’s Fengyun-3E (FY-3E) GNOS-II Global Navigation Satellite System Reflectometry (GNSS-R) for bipolar Sea Ice Concentration (SIC) retrieval.

Study Configuration

• Spatial Scale: Bipolar regions (Arctic and Antarctic), including ice-water boundary zones, with native GNSS-R observation resolution of approximately 1 km × 6 km, aggregated into monthly composites for spatial distribution analysis.
• Temporal Scale: Individual GNSS-R observation times, aggregated into monthly composites due to limited daily spatial coverage.

Methodology and Data

• Models used: Random Forest Regression (RFR) model with a rolling-window training strategy, integrated with regional partitioning and dynamic thresholding for sea ice detection.
• Data sources: Reflected signals from Fengyun-3E (FY-3E) GNOS-II Global Navigation Satellite System Reflectometry (GNSS-R) Delay Doppler Maps (DDMs); reference Sea Ice Concentration (SIC) data from the OSI SAF Special Sensor Microwave Imager Sounder (SSMIS).

Main Results

• The study successfully demonstrates the feasibility and accuracy of GNSS-R-based SIC retrieval for both polar regions.
• For the testing set, the average correlation coefficient (R) is 0.9450 in the Arctic and 0.9602 in the Antarctic.
• Corresponding Root Mean Squared Error (RMSE) values are 0.1262 in the Arctic and 0.0818 in the Antarctic.
• In challenging ice–water transition zones, RMSE values remain acceptable, reaching 0.1486 in the Arctic and 0.1404 in the Antarctic.

Contributions

• Presents the first comprehensive investigation of China’s Fengyun-3E (FY-3E) GNOS-II GNSS-R for bipolar Sea Ice Concentration (SIC) retrieval.
• Develops a robust and effective GNSS-R-based approach for cryospheric monitoring at high latitudes in both polar regions.
• Validates the accuracy and feasibility of FY-3E GNOS-II GNSS-R data for SIC estimation across extensive datasets in both Arctic and Antarctic regions.

Funding

• Not specified in the provided text.

Citation

@article{Xie2026Sea,
  author = {Xie, Tingyu and Yin, Cong and Bai, Weihua and Song, Di and Huang, Feixiong and Xia, Junming and Zhai, Xiaochun and Sun, Yueqiang and Du, Qifei and Wang, Bin},
  title = {Sea Ice Concentration Retrieval in the Arctic and Antarctic Using FY-3E GNSS-R Data},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18020285},
  url = {https://doi.org/10.3390/rs18020285}
}