12 citations as recorded by crossref.

1. Pan-Arctic sea ice concentration from SAR and passive microwave T. Wulf et al. https://doi.org/10.5194/tc-18-5277-2024
2. High Resolution Sea Ice Concentration Using a Sentinel-1 U-Net Ice-Water Classifier J. Rusin et al. https://doi.org/10.1109/JSTARS.2025.3553623
3. A Method for Predicting Arctic Sea Ice Concentration Based on Multimodal Feature Fusion and Temporal Trend Analysis L. Huang et al. https://doi.org/10.3390/jmse14110993
4. Seasonal Variability of Sea Ice Bulk Density During the MOSAiC Expedition: Results From Synergistic In Situ, Airborne, and Satellite Observations Y. Zhou et al. https://doi.org/10.1109/TGRS.2025.3650353
5. A decade of sea ice concentration retrieved from sentinel-1 T. Wulf et al. https://doi.org/10.1016/j.rse.2026.115252
6. Formation and fate of freshwater on an ice floe in the Central Arctic M. Smith et al. https://doi.org/10.5194/tc-19-619-2025
7. Toward Higher Resolution Arctic Winter Sea Ice Concentration: Addressing Sentinel-1 Misclassification With AMSR2 Data Fusion J. Rusin et al. https://doi.org/10.1109/JSTARS.2026.3676222
8. MFDA: Unified Multi-Task Architecture for Cross-Scene Sea Ice Classification Y. Chen et al. https://doi.org/10.1109/TGRS.2024.3491190
9. Sea Ice Classification Enhancement Using Calibration-Focused Loss Functions N. Ahmadian et al. https://doi.org/10.3390/rs18050810
10. Impacts of air fraction increase on Arctic sea ice density, freeboard, and thickness estimation during the melt season E. Salganik et al. https://doi.org/10.5194/tc-19-1259-2025
11. Sea ice freeboard extrapolation from ICESat-2 to Sentinel-1 K. Kortum et al. https://doi.org/10.5194/tc-19-4701-2025
12. An Arctic Sea Ice Thickness Inversion Method Based on Deep Learning Two-Branch Architecture and Multisource Remote Sensing Data Fusion R. Huang et al. https://doi.org/10.1109/JSTARS.2025.3636999