OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation
This work addresses ocean monitoring for remote sensing applications, but it is incremental as it builds on a previous release.
The paper tackles the problem of ocean observation using SAR data by introducing OceanSAR-2, an improved foundation model that enhances performance and reduces training costs, achieving strong transfer across tasks like geophysical pattern classification and iceberg detection.
We present OceanSAR-2, the second generation of our foundation model for SAR-based ocean observation. Building on our earlier release, which pioneered self-supervised learning on Sentinel-1 Wave Mode data, OceanSAR-2 relies on improved SSL training and dynamic data curation strategies, which enhances performance while reducing training cost. OceanSAR-2 demonstrates strong transfer performance across downstream tasks, including geophysical pattern classification, ocean surface wind vector and significant wave height estimation, and iceberg detection. We release standardized benchmark datasets, providing a foundation for systematic evaluation and advancement of SAR models for ocean applications.