Beach Slopes From Satellite‐Derived Shorelines

The steepness of the beach face is a fundamental parameter for coastal morphodynamic research. Despite its importance, it remains extremely difficult to obtain reliable estimates of the beach‐face slope over large spatial scales (thousands of km of coastline). In this letter, a novel approach to estimate this slope from time series of satellite‐derived shoreline positions is presented. This new technique uses a frequency domain analysis to find the optimum slope that minimizes high‐frequency tidal fluctuations relative to lower‐frequency erosion/accretion signals. A detailed assessment of this new approach at eight locations spanning a range of tidal regimes, wave climates, and sediment grain sizes shows strong agreement (R2= 0.93) with field measurements. The automated technique is then applied across thousands of beaches in eastern Australia and California, USA, revealing similar regional‐scale distributions along these two contrasting coastlines and highlights the potential for new global‐scale insight to beach‐face slope spatial distribution, variability, and trends. How steep a beach is can dictate the way the beach interacts with the incoming ocean waves and therefore is of paramount importance for coastal scientists and engineers, coastal flood modelers, and swim safety officers. However, despite its importance, it is impractical to obtain reliable estimates of the “typical” beach‐face slope along large lengths of sandy coastlines (hundreds to thousands of km) because of the logistics that would be necessary to visit many sites repeatedly to obtain these measurements. This letter describes a new technique to estimate the beach‐face slope in the absence of field observations, relying instead on long‐term publicly available satellite observations and a global tide model. This technique is then applied to thousands of beaches along the coastlines of eastern Australia and California in the United States. A novel remote sensing technique to estimate beach‐face slopes from satellite imagery and modeled tides is presentedTime series of shoreline change are transformed into frequency domain to find the slope that minimizes high‐frequency tidal fluctuationsValidation against in situ data shows high accuracy across sites ranging in grain size, tidal range, and wave climate