SWOT-Based Intertidal Digital Elevation Model Extraction and Spatiotemporal Variation Assessment

Traditional methods for the construction of intertidal digital elevation models (DEMs) require the integration of long-term multi-sensor datasets and struggle to capture the spatiotemporal variation caused by ocean dynamics. The SWOT (surface water and ocean topography) mission, with its wide-swath interferometric altimetry technology, provides instantaneous full-swath elevation data in a single pass, offering a revolutionary data source for high-precision intertidal topographic monitoring. This study presents a framework for SWOT-based intertidal DEM extraction that integrates data preprocessing, topographic slope map construction, and tidal channel masking. The radial sand ridge region along the Jiangsu coast is analyzed using SWOT L2 LR (Low Resolution) unsmoothed data from July 2023 to December 2024. Multisource validation data are used to comprehensively assess the accuracy of sea surface height (SSH) and land elevation derived from LR products. Results show that the root mean square error (RMSE) of SSH at Dafeng, Yanghe, and Gensha tide stations is 0.25 m, 0.19 m, and 0.32 m, respectively. Validation with LiDAR data indicates a land elevation accuracy of ~0.3 m. Additionally, the topographic features captured by LR products are consistent with the patterns observed in the remote sensing imagery. A 16-month time-series analysis reveals significant spatiotemporal variations in the Tiaozini area, particularly concentrated in the tidal channel areas. Furthermore, the Pearson correlation coefficient for the DEMs generated from SWOT data decreased from 0.94 over a one-month interval to 0.84 over sixteen months, reflecting the persistent impact of oceanic dynamic processes on intertidal topography.