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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., Coastal Engineering

The sensitivity of a one-line longshore shoreline change model to the incident wave direction is evaluated at Narrabeen Beach (Australia). As previously observed, the application of the one-line model using wave conditions generated along the 10-m depth contour produces a long-term reorientation of the coastline, with an initial transition period and then a new stable equilibrium during the 10-year period from 2005 to 2015. However, this coastline change in shoreline planform shape is not observed in the shoreline position measurements. The source of this error is investigated by assuming that it is caused by biases in the incident wave direction and by using a Monte Carlo approach to search for the optimal set of wave angle bias corrections to apply at each cross-shore transect. The obtained optimal values enable the one-line model to reproduce accurately the shoreline planform, and they are coherent with estimates of the wave breaking angle obtained independently using a nearshore wave propagation model. Then, using the corrected wave angle time series as a reference, a second Monte Carlo analysis is completed to investigate the sensitivity of the model to errors in the mean wave direction drawn from Gaussian distributions with varying standard deviations. The analysis shows the range of expected errors in shoreline position for an estimated range of errors in the mean wave direction at Narrabeen beach. This work highlights the importance of considering the sensitivity of one-line longshore model simulations to errors in the incident wave angle, which can be relatively large given the uncertainties in spectral wave model estimates of wave direction, in wave buoy observations, and in wave propagation methods or input bathymetry used to estimate wave breaking conditions.