Sea Surface Current Vector Reconstruction from Multitemporal Sentinel-1 Doppler Observations: A Trajectory-Crossing Approach with Spatial Registration
Synthetic aperture radar (SAR) provides high-resolution observations of radial sea surface currents. By combining radial currents observed from different viewing directions, the trajectory-crossing method can reconstruct the sea surface current vector field. In practice, observations from ascending and descending passes are acquired at different times, so the spatial structure of the surface current field may evolve between acquisitions. Directly combining multitemporal observations can therefore introduce spatial mismatch and reduce reconstruction accuracy. This study proposes a trajectory-crossing method for reconstructing sea surface current vectors from multitemporal Sentinel-1 Doppler observations. Maximum cross-correlation (MCC) is applied to gradient images of the radial current fields to estimate displacement and spatially register observations acquired at different times before vector reconstruction. The method is evaluated using Sentinel-1 data acquired over the Gulf Stream region and compared with geostrophic currents from the Copernicus Marine Environment Monitoring Service (CMEMS), Surface Water and Ocean Topography (SWOT) observations, and Global Drifter Program (GDP) drifter measurements. Results show that the proposed method reduces mismatch effects and improves the accuracy and stability of sea surface current vector reconstruction. It provides a practical approach for deriving surface current vector fields from multitemporal SAR Doppler observations.
Authors
- Yawei Zhao (ORCID: https://orcid.org/0000-0003-0765-1933)
- Wenjia Zhao (ORCID: https://orcid.org/0000-0002-9238-6881)
- Haimei Mo
- Jinsong Chong (ORCID: https://orcid.org/0000-0002-0840-1234)
- JINCHENG DENG
- Lebao Yang
Institutions
- Chinese Academy of Sciences (CN)
- Aerospace Information Research Institute (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-09-16
- DOI
- https://doi.org/10.3390/rs18183192
- Primary Topic
- Ocean Waves and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00