This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.
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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 (SDS) 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 SDS 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 SDS algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.
DOI
https://doi.org/10.31223/X58W98
Subjects
Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Physical Sciences and Mathematics
Keywords
satellite-derived shorelines, Landsat, sentinel-2, Google Earth Engine, Coastal erosion, Benchmarking, beaches, satellites, remote sensing, Optical Imagery, algorithm intercomparison
Dates
Published: 2023-07-10 03:43
Last Updated: 2023-07-10 15:03
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License
CC BY Attribution 4.0 International
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Conflict of interest statement:
None
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