LogiTide2DEM: A method for reconstructing intertidal topography in complex tidal flats using logistic regression with multi-temporal Sentinel-2 and Landsat imagery

Abstract

Intertidal zones are transitional areas between marine and terrestrial systems and are significant for ecological systems, socio-economic activities, and coastal erosion mitigation. However, intertidal topography is often degraded and lost by natural coastal processes and anthropogenic impacts. Accurate and frequent mapping of intertidal topography is essential for effective coastal management. Previous studies have relied on ground-based surveys or shoreline method using satellite imagery to measure intertidal topography, but these approaches are often limited in spatial extent and temporal resolution. To address these limitations, we propose LogiTide2DEM, a novel method for reconstructing intertidal topography. This method uses logistic regression to determine optimal tide heights for water-land differentiation as surface elevation using multi-temporal Sentinel-2 and Landsat imagery. The advantages of LogiTide2DEM include: a pixel-based approach rather than shoreline methods, elevation constraints using tidal height records, adaptive elevation estimation using logistic regression, and integrated quality assessment of topographic data. We applied and validated LogiTide2DEM on the Changhua coast in central-western Taiwan, reconstructing 22 years (2002–2023) of intertidal topography. Results show root-mean-square differences in elevation ranging from 0.24 m to 0.59 m, with the ratio of mean absolute error to the DEM elevation range between 11 % and 13 %, and correlation coefficients of 0.69 to 0.81. Despite a moderate omission error in water-land classification, LogiTide2DEM demonstrates robust performance in reconstructing intertidal topography. This study shows the capability of LogiTide2DEM to generate high-resolution, reliable topography spanning past decades, providing valuable insights for coastal management and research.