23 citations as recorded by crossref.

1. Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. https://doi.org/10.3390/rs12071214
2. Mapping the thickness of sea ice in the Arctic as an example of using data from a ship-based television complex for operational hydrometeorological support of maritime activities E. Afanasyeva et al. https://doi.org/10.30758/0555-2648-2022-68-2-96-117
3. S3MPC: Improvement on Inland Water Tracking and Water Level Monitoring from the OLTC Onboard Sentinel-3 Altimeters N. Taburet et al. https://doi.org/10.3390/rs12183055
4. Sensitivity of Radar Altimeter Waveform to Changes in Sea Ice Type at Resolution of Synthetic Aperture Radar W. Aldenhoff et al. https://doi.org/10.3390/rs11222602
5. Assessment of Arctic Sea Ice Classification Ability of Chinese HY-2B Dual-Band Radar Altimeter During Winter to Early Spring Conditions X. Zhang et al. https://doi.org/10.1109/JSTARS.2021.3114228
6. Comparative Evaluation of Sea Ice Lead Detection Based on SAR Imagery and Altimeter Data N. Longepe et al. https://doi.org/10.1109/TGRS.2018.2889519
7. Supplementing Remote Sensing of Ice: Deep Learning-Based Image Segmentation System for Automatic Detection and Localization of Sea-ice Formations From Close-Range Optical Images N. Panchi et al. https://doi.org/10.1109/JSEN.2021.3084556
8. Classification of Sea Ice Types in the Arctic by Radar Echoes from SARAL/AltiKa R. Fredensborg Hansen et al. https://doi.org/10.3390/rs13163183
9. Sea ice recognition for CFOSAT SWIM at multiple small incidence angles in the Arctic M. Liu et al. https://doi.org/10.3389/fmars.2022.986228
10. Estimation of Arctic Sea Ice Thickness Using HY-2B Altimeter Data C. Pang et al. https://doi.org/10.3390/rs16234565
11. Machine learning based classification of lake ice and open water from Sentinel-3 SAR altimetry waveforms J. Mugunthan et al. https://doi.org/10.1016/j.rse.2023.113891
12. Assessment of Satellite Altimetric and Compact Polarimetric SAR Parameters Over Early Spring Snow-Covered Landfast Sea Ice in the Canadian Arctic H. Lam et al. https://doi.org/10.1109/JSTARS.2025.3595821
13. Assessing spatiotemporal variability in melt–refreeze patterns in firn over Greenland with CryoSat-2 W. Li et al. https://doi.org/10.5194/tc-19-3419-2025
14. Lead detection using Cryosat-2 delay-doppler processing and Sentinel-1 SAR images M. Passaro et al. https://doi.org/10.1016/j.asr.2017.07.011
15. Sea Ice Classification Using Cryosat-2 Altimeter Data by Optimal Classifier–Feature Assembly X. Shen et al. https://doi.org/10.1109/LGRS.2017.2743339
16. Estimating Arctic sea ice thickness and volume using CryoSat-2 radar altimeter data R. Tilling et al. https://doi.org/10.1016/j.asr.2017.10.051
17. Discrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF) S. Shu et al. https://doi.org/10.1080/01490419.2019.1671560
18. Arctic Sea Ice Classification Based on CFOSAT SWIM Data at Multiple Small Incidence Angles M. Liu et al. https://doi.org/10.3390/rs14010091
19. Monitoring Arctic thin ice: a comparison between CryoSat-2 SAR altimetry data and MODIS thermal-infrared imagery F. Müller et al. https://doi.org/10.5194/tc-17-809-2023
20. Near-real-time Arctic sea ice thickness and volume from CryoSat-2 R. Tilling et al. https://doi.org/10.5194/tc-10-2003-2016
21. A Study of the Technology Used to Distinguish Sea Ice and Seawater on the Haiyang-2A/B (HY-2A/B) Altimeter Data C. Jiang et al. https://doi.org/10.3390/rs11121490
22. Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data A. Gegiuc et al. https://doi.org/10.5194/tc-12-343-2018
23. A New Retracking Algorithm for Retrieving Sea Ice Freeboard from CryoSat-2 Radar Altimeter Data during Winter–Spring Transition X. Shen et al. https://doi.org/10.3390/rs11101194