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Tidal flat topography provides crucial insights for understanding tidal flatsand their dynamic evolution. However, the wide-ranging and rapidly changingnature of tidal flats, which are periodically submerged in shallow water, posechallenges for many current monitoring methods in terms of both efficiency andprecision. In this study, we considered the dynamic process of tidal flatsubmergence and utilized time-series Sentinel-2 images on Google Earth Engine(GEE) to calculate the tidal flat exposure frequency. This information was usedto determine the spatial extent of the tidal flats, and subsequently, byemploying ICESat-2 data, we established a 1D-linear regression model based onelevation and frequency values, which realizes the inversion of the tidal flatelevation within Cixi City. The study shows the following: (1) the tidal flatexposure frequency and ICESat-2 elevation data exhibit a strong positivecorrelation (R2=0.85); (2) the tidal flat area within Cixi City is 115.81 km2,and the overall accuracy is 95.36%; and (3) the elevation range of the tidalflats in the study area is between -0.42 and 2.73 m, and the mean absoluteerror (MAE) is 0.24 m. Additionally, we consider that the temporal resolutionof remote sensing imagery plays a crucial role in determining the accuracy ofthe elevation inversion, and we found that higher tidal flats exhibit betterinversion accuracy than lower tidal flats.

Mapping tidal flat topography using time-series Sentinel-2 images and ICESat-2 data: A case study in Cixi City