If coral reefs continue to degrade, waves on coastlines may substantially increase, leading to greater coastal erosion.

Beaches are characterized by high morphodynamic activity, and high-frequency measurements are needed to understand their states and rates of change. Ideally, beach survey methods should be at once accurate, rapid and low-cost. Recently, unmanned aerial systems (drones) have been increasingly utilized to measure beach topography. In this paper, we present a review of the state of art in drones and photogrammetry for beach surveys and the respective achieved measurement quality (where reported). We then show how drones with a minimal configuration and a low-cost setup can meet the high accuracy and rapidity required for beach surveys. To test a minimal drone and ground control point configuration, we used consumer-grade equipment to perform the same flight path with different cameras and at different altitudes. We then used photogrammetry to produce digital elevation models of the beach. Using a GNSS-RTK system, we collected 2950 independent control points to evaluate the accuracy of the digital elevation models. Results show that, once a few potential sources of uncertainties in the final digital elevation model are taken into account, the average RMSE(z) of the digital elevation models was ~5 cm, with a survey efficiency of ca. 3 m² min⁻¹. Digital elevation models taken at different times were used to calculate the before–after sediment budget following a storm that hit a sandy coast in Sylt Island at the German North Sea coast.

Low-altitude high-resolution aerial photographs allow for the reconstruction of structural properties of shallow coral reefs and the quantification of their topographic complexity. This study shows the scope and limitations of two-media (air/water) Structure from Motion—Multi-View Stereo reconstruction method using drone aerial photographs to reconstruct coral height. We apply this method in nine different sites covering a total area of about 7000 m², and we examine the suitability of the method to obtain topographic complexity estimates (i.e., seafloor rugosity). A simple refraction correction and survey design allowed reaching a root mean square error of 0.1 m for the generated digital models of the seafloor (without the refraction correction the root mean square error was 0.2 m). We find that the complexity of the seafloor extracted from the drone digital models is slightly underestimated compared to the one measured with a traditional in situ survey method.