UAS-Based Mapping of Nearshore Bathymetry Using PIV-POD Under Complex Wave Conditions

Abstract

This study presents a novel method for nearshore bathymetry estimation derived from Unmanned Aerial System (UAS) video imagery. Field experiments were conducted on a low-energy sandy barred beach located in the northern Yucatan Peninsula (Sisal, Mexico). UAS flights covered an 800 m stretch of coast in December 2022 during prevailing sea-breeze conditions, which drove short-crested, high-incidence-angle sea waves. A dual-method approach, based on the linear dispersion relationship, was used to estimate bathymetry from the UAS imagery. Particle Image Velocimetry (PIV) was employed to measure the celerity of breaking wave crests in the surf zone, while the Proper Orthogonal Decomposition (POD) method was applied to extract wavelengths and wave periods outside the surf zone. The approach involves deriving these wave parameters and calculating bathymetry, including the influence of ambient currents. UAV-derived bathymetry was validated against ground-truth GPS measurements in shallow waters ( h < 1.5 m), where the combined method yielded an overall root-mean-square error (RMSE) of 0.20 m. The method was extended offshore ( h > 1.5 m) to reconstruct the nearshore bathymetry. The operational range of the depth inversion demonstrated in this study is kh < 1.2. Moreover, cross-shore variation of alongshore surf zone currents was also satisfactorily estimated. The proposed methodology successfully demonstrates the potential and limitations of UAS-based imaging for high-resolution mapping of coastal bathymetry and surf zone hydrodynamics during complex wave conditions.