Accuracy test of satellite imagery-derived bathymetry in shallow waters using Sentinel-2A multispectral imagery
DOI: https://doi.org/10.3846/gac.2025.21128Abstract
Continuous bathymetry mapping for shallow waters is very important considering that these waters are prone to change. Bathymetry measurements obtained from satellite imagery are an alternative that can be used. This study aimed to evaluate and develop algorithms that can be used to estimate shallow water depth values obtained from satellite imagery. In this study, the depth mapping results were obtained from Surface Reflectance derived from Sentinel-2A image processing. A comparative analysis was performed by comparing measurements obtained with an echosounder and estimated depths estimated with Lyzenga, Stumpf, and modified Stumpf algorithms. In this study, where the depth ranged from 2–6 meters, the Lyzenga algorithm performed the best algorithm with the R2 value of 0.94 and the RMSE 0.23, followed by the modified Stumpf algorithm with an R2 value of 0.93 and RMSE 0.24, and Stumpf algorithm with a R2 value of 0.88 and a RMSE of 0.32. Overall, this study provides an important contribution to comparing Lyzenga and Stumpf algorithms for estimating water depths. This study provides guidance on choosing the correct algorithm for bathymetric mapping using satellite imagery in similar water locations.
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satellite derived bathymetry, shallow water, Google Earth Engine, satellite imaging, Sentinel-2A, statistical modellingHow to Cite
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Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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