12 citations as recorded by crossref.

1. A Novel Object-Oriented Rotated Intensity Matching Method for Iceberg Drift Monitoring With SAR Images C. Wang et al. https://doi.org/10.1109/LGRS.2024.3418834
2. Evolution of the dynamics, area, and ice production of the Amundsen Sea Polynya, Antarctica, 2016–2021 G. Macdonald et al. https://doi.org/10.5194/tc-17-457-2023
3. Tracking of the huge Antarctic iceberg A-76 M. Moctezuma-Flores et al. https://doi.org/10.1080/2150704X.2022.2152292
4. Fragmentation patterns of Antarctic icebergs in sea ice: observations and statistical data Z. Guan et al. https://doi.org/10.1080/17538947.2025.2511289
5. Evolution of supraglacial lakes on Sermeq Avannarleq glacier, Greenland using Google Earth Engine D. Zhu et al. https://doi.org/10.1016/j.ejrh.2022.101246
6. Mapping gully affected areas by using Sentinel 2 imagery and digital elevation model based on the Google Earth Engine X. Huang et al. https://doi.org/10.1016/j.catena.2023.107473
7. Automated detection and tracking of medium-large icebergs from Sentinel-1 imagery using Google Earth Engine Y. Koo et al. https://doi.org/10.1016/j.rse.2023.113731
8. Tracking Large Tabular Icebergs in Antarctica Using AMSR2 Observations and Random Forest: A Case Study of A23A M. Cho et al. https://doi.org/10.7780/kjrs.2025.41.2.1.8
9. Mapping the extent of giant Antarctic icebergs with deep learning A. Braakmann-Folgmann et al. https://doi.org/10.5194/tc-17-4675-2023
10. Icebergs, jigsaw puzzles, and genealogy: automated multi-generational iceberg tracking and lineage reconstruction B. Evans et al. https://doi.org/10.5194/tc-20-467-2026
11. Ocean Remote Sensing Techniques and Applications: A Review (Part II) M. Amani et al. https://doi.org/10.3390/w14213401
12. Unsupervised machine learning detection of iceberg populations within sea ice from dual-polarisation SAR imagery B. Evans et al. https://doi.org/10.1016/j.rse.2023.113780