Abstract's details
SWOT-based intertidal topography retrieval using mission-only data: validation and potential applications
Event: 2025 SWOT Science Team Meeting
Session: Afternoon Plenary Session: Deltas, Estuaries and Coasts
Presentation type: Oral
While the SWOT altimetry mission is primarily designed to observe open ocean and inland water bodies, recent studies (Salameh et al., 2024; Shi et al., 2025) have demonstrated its potential for mapping intertidal topography during low tide observations. One of the main challenges in utilizing SWOT for intertidal applications, such as bathymetry extraction, lies in accurately distinguishing intertidal pixels from water pixels. The current SWOT pixel classification does not include any dedicated intertidal class. This study introduces a new methodology for identifying intertidal pixels only using SWOT data, without relying on external datasets.
To validated both the methodology of intertidal classification and the quality of SWOT-derived intertidal topography, we focus on the complex, macro-tidal (1.5 m to 5.5 m tidal range) coastal region of Pertuis Charentais, located within Bay of Biscay, France. This area lies within two SWOT passes (348, 419) with both ocean based LR and inland based HR data coverage and is covered by a rich set of in-situ observations, including high-resolution LiDAR topography and tide gauges. Using the in-situ LiDAR data as a reference, we assessed the accuracy and the reliability of SWOT-derived intertidal topography dataset across a range of intertidal environments within the validation zone. Our findings highlight SWOT’s strong potential for capturing the spatiotemporal evolution of the dynamic intertidal zones worldwide. Furthermore, our approach offers a cost-effective pathway for monitoring intertidal bathymetry with accuracy comparable to expensive LiDAR-based measurements. This advancement will significantly enhance coastal monitoring, improved numerical modeling, particularly in the data-sparse regions.
Reference:
Salameh, E., Desroches, D., Deloffre, J., Fjørtoft, R., Mendoza, E. T., Turki, I., Froideval, L., Levaillant, R., Déchamps, S., Picot, N., Laignel, B., & Frappart, F. (2024). Evaluating SWOT’s interferometric capabilities for mapping intertidal topography. Remote Sensing of Environment, 314, 114401. https://doi.org/10.1016/j.rse.2024.114401
Shi, H., Jia, D., He, X., Andersen, O. B., & Zheng, X. (2025). SWOT-Based Intertidal Digital Elevation Model Extraction and Spatiotemporal Variation Assessment. Remote Sensing, 17(9), Article 9. https://doi.org/10.3390/rs17091516
Back to the list of abstractTo validated both the methodology of intertidal classification and the quality of SWOT-derived intertidal topography, we focus on the complex, macro-tidal (1.5 m to 5.5 m tidal range) coastal region of Pertuis Charentais, located within Bay of Biscay, France. This area lies within two SWOT passes (348, 419) with both ocean based LR and inland based HR data coverage and is covered by a rich set of in-situ observations, including high-resolution LiDAR topography and tide gauges. Using the in-situ LiDAR data as a reference, we assessed the accuracy and the reliability of SWOT-derived intertidal topography dataset across a range of intertidal environments within the validation zone. Our findings highlight SWOT’s strong potential for capturing the spatiotemporal evolution of the dynamic intertidal zones worldwide. Furthermore, our approach offers a cost-effective pathway for monitoring intertidal bathymetry with accuracy comparable to expensive LiDAR-based measurements. This advancement will significantly enhance coastal monitoring, improved numerical modeling, particularly in the data-sparse regions.
Reference:
Salameh, E., Desroches, D., Deloffre, J., Fjørtoft, R., Mendoza, E. T., Turki, I., Froideval, L., Levaillant, R., Déchamps, S., Picot, N., Laignel, B., & Frappart, F. (2024). Evaluating SWOT’s interferometric capabilities for mapping intertidal topography. Remote Sensing of Environment, 314, 114401. https://doi.org/10.1016/j.rse.2024.114401
Shi, H., Jia, D., He, X., Andersen, O. B., & Zheng, X. (2025). SWOT-Based Intertidal Digital Elevation Model Extraction and Spatiotemporal Variation Assessment. Remote Sensing, 17(9), Article 9. https://doi.org/10.3390/rs17091516