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Sea ice thickness (SIT) is a critical parameter for polar navigation and operational safety, yet existing observations remain limited in spatial resolution, timeliness, or field accessibility. This study presents a rapid, high-resolution unmanned aerial vehicle (UAV) LiDAR workflow for SIT retrieval using point cloud data acquired during the Following Arctic/Antarctic iCE 2024 (FACE2024) Expedition aboard the R/V Zhong Shan Da Xue Ji Di. The workflow integrates point cloud preprocessing, local sea-surface elevation estimation, point cloud classification, snow freeboard calculation, and hydrostatic conversion. The resulting SIT has a 0.1 m grid resolution and ranges from approximately 0.30 to 3.12 m, with a mean thickness of 1.52 m. Eight contemporaneous drilling measurements over level ice yielded a mean thickness of 1.535 m, providing an illustrative station-scale field reference for the retrieved thickness magnitude. The retrieved freeboard and SIT distributions resolve fine-scale spatial variability across the surveyed ice field, including ridge-like and locally deformed features. These results demonstrate the feasibility of UAV-borne LiDAR for rapid, localized, high-resolution SIT mapping and support its potential for near-real-time field applications in Arctic sea ice observations.
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Feng et al. (2026) studied this question.
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