Delta-Scale 10-m Tidal Flat Topography Reconstruction: A Transferable Deep Learning Approach Using Sentinel-2 Time Series

Le résumé fourni par la source

Reliable tidal flat elevation data with a resolution better than 30 meters is vital for understanding macro-scale sedimentation processes and storm surge erosion in estuarine deltas. However, the highly dynamic and turbid environments of global estuaries pose significant challenges for traditional manual or unmanned aerial vehicle (UAV) methods in delta-scale monitoring. Insufficient elevation data currently hinders sea-level rise modeling and coastal management for the world’s densely populated, flood-prone river deltas. There is an urgent need to characterize and reconstruct the vertical geomorphology of tidal flats through improved observations and modeling. In this study, we propose a robust tidal flat topography mapping framework using freely available satellite imagery and deep learning. First, we developed an enhanced U-Net model to delineate land–water boundaries and generate inundation frequency maps from time-series Sentinel-2 imagery. A regionally adaptive nonlinear inversion model was then constructed using inundation frequency and ICESat-2 elevation data, allowing us to generate a 10-m resolution tidal flat DEM of the Yellow River estuary. The deep learning model achieved an F1-score of 0.96, and the resulting DEM showed strong agreement with UAV LiDAR data, yielding a root mean square error (RMSE) of 0.18 m. The reconstructed elevations range from -0.51 m to 0.96 m, exhibiting a spatial gradient of lower elevations in the north and higher elevations in the southern and eastern sectors. To assess transferability, we applied the method to the Radial Sand Ridge System in the South Yellow Sea. The model achieved a comparable RMSE of 0.52 m without re-training, demonstrating robust generalization across different estuarine environments. This study provides a cost-effective framework for monitoring coastal geomorphological changes and helps fill the data gap in delta-scale topographic mapping for global intertidal zones.

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