Benchmarking satellite-derived shoreline mapping algorithms

• Published in: Communications Earth & Environment
• Main Authors: K. Vos, K. D. Splinter, J. Palomar-Vázquez, J. E. Pardo-Pascual, J. Almonacid-Caballer, C. Cabezas-Rabadán, E. C. Kras, A. P. Luijendijk, F. Calkoen, L. P. Almeida, D. Pais, A. H. F. Klein, Y. Mao, D. Harris, B. Castelle, D. Buscombe, S. Vitousek
• Format: Article
• Language: English
• Published: Nature Portfolio 2023-09-01
• Online Access: https://doi.org/10.1038/s43247-023-01001-2

Abstract Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.