Communications Earth & Environment (Sep 2023)

Benchmarking satellite-derived shoreline mapping algorithms

  • 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

DOI
https://doi.org/10.1038/s43247-023-01001-2
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 17

Abstract

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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.