Satellite-derived bathymetry using Sentinel-2 in mesotidal coasts

Abstract

Coastal zones are strategic environments of high socioeconomic, political, and ecological value, with over half of the world's population residing within 200 km of the coast. This proximity highlights their vulnerability to extreme events, which are exacerbated by global changes, leading to significant coastal impacts such as erosion, flooding, and ecosystem services deterioration. Consequently, efficient and operational methodologies for continuous monitoring are urgently needed to face these challenges. Bathymetric data are essential for understanding coastal dynamics, yet traditional data collection methods are often constrained by logistical challenges and high costs. Spaceborne remote sensing techniques offer significant advantages over traditional ground-based methods, particularly in terms of cost-effectiveness and operational efficiency. Over the last half-century, different Satellite-derived bathymetry (SDB) methodologies have been developed; however, challenges still persist. In this research, we applied a robust SDB methodology to three different study sites: Cíes Islands, Baiona Bay, and Vao beach within the Ría de Vigo, Galicia (NW Spain). These areas offer diverse and complex mesotidal environments to test for the very first time the methodology's efficacy. SDB was retrieved with a median absolute error (MedAE) ranging from 0.35 m to 1.55 m for depths up to 14 m. Results with different data source were evaluated, obtaining MedAE for nautical charts ranging from 0.46 m to 1.55 m. The precision between the data sources were quite close. In addition, multi-image composite was generated using images coinciding with both low tide (LT) and high tide (HT) conditions across the three zones. The lowest MedAE values were consistently obtained in images classified as LT (0.46 m) corresponding to Vao area. The results highlight the potential of nautical charts as a reliable source of calibration data for SDB, confirm the effectiveness of multi-image and switching models to correct artifacts and turbidity, considering tidal effects, improving single image approaches, and leverage visible bands for precise depth retrieval under varying conditions.