Beach Slopes From Satellite‐Derived Shorelines

Abstract

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.

Coastal Wetland Shoreline Change Monitoring: A Comparison of Shorelines from High-Resolution WorldView Satellite Imagery, Aerial Imagery, and Field Surveys

“…Shoreline position was not adjusted to water level prior to rate of change analyses and therefore the higher rates of change may be a product of changing water level conditions. Other studies applied water level corrections to satellite-derived beach shorelines [31,53], but we could not find examples where similar corrections were applied to vegetated shorelines. Other variables, such as vegetation and soil characteristics, could impact both sensor detection of shoreline position and distance of inundation, therefore we used a conservative estimate of marsh slope to avoid over-correction and provide our analysis to demonstrate the need to consider these impacts on results.…”

“…The mixed shoreline type (vegetation and beach) is not a unique feature to Grand Bay and can be found frequently in other estuarine and marsh-dominated coastlines; therefore, a methodology that adopts a mixed analysis approach to address multiple shorelines types would be more appropriate for regional or national estuarine shoreline mapping programs. The simple method used here can be improved in light of other research that use high-resolution imagery (WV and other satellite data) to delineate beach shorelines [22,31,53], which may provide a method to improve delineations of wetland shorelines that are bordered by sandy beach. In addition, we discovered an NDVI value of 0.21 consistently provided an adequate representation of the shoreline (vegetation-water boundary) for coastal marsh habitat of southern Mississippi.…”

“…In addition, water level can impact marsh shoreline detection by either obscuring the shoreline (inundating the marsh when water level is high) or confusing detection by exposing nearshore vegetation, such as sparse marsh grasses or seagrass blades. We could find no simple method for correcting shoreline vector position for water level, so we developed the following technique, modified from methods developed for beach environments [53]. If water level was above the marsh platform elevation (determined as the mean of the marsh platform elevation data, data collection described in Section 2.2.1), a simple correction was applied to adjust the horizontal difference between the two shoreline vectors using the following Equation (3):…”

Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones

“…However, shorelines derived from space are difficult to validate in-situ, consequently, only a few studies used ancillary beach topographic data or coincident shoreline GPS surveys to test the accuracy of the extracted shorelines [56][57][58][59] . Moreover, sandy beaches topographic features such as beachface slope 60 , intertidal extent 61 and elevation 62,63 at continental-scale have also started to be derived from space-based observations. These methods need beach topographic data at higher resolution to be validated against.…”

Reinterpreting the Bruun Rule in the Context of Equilibrium Shoreline Models

“…The foreshore beach slope, which is adopted in the current model, does not require the estimation of active beach boundaries and can be extracted from topographic profiles (regular enough to account for potential temporal and spatial variability) that can be more easily surveyed by various means at a low cost. Further, recently developed satellite-remote sensing techniques to derive foreshore beach slopes over large scales [62] may represent a promising complement to the model developed here. Thus, the ESMs combined with SLR-driven recession (including feedbacks) may result in reduced uncertainty in long-term shoreline change and a potential of application to a much wider range of coasts compared to the models based on the linear sum of the Bruun and ESM projections.…”