Aeolian transport affects beach and foredune pre-storm morphologies, which directly contribute to storm responses. However, significant spatiotemporal variation exists within beach-dune systems regarding how biotic and abiotic factors affect topography. There are multiple metrics for quantifying topographic change, with varying pros and cons, but understanding how a system changes across spatiotemporal scales relative to varying forcings is necessary to accurately model and more effectively manage these systems. Beach and foredune micro- and mesoscale elevation changes (Δz) were quantified remotely and in situ across a mid-Atlantic coastal system. The microscale field collections consisted of 27 repeat measurements of 73 elevation pins located in vegetated, transitional, and unvegetated foredune microhabitats over three years (2015 to 2018) during seasonal, event-based, and background wind-condition collections. Unoccupied aerial System (UAS) surveys were collected to link microscale point Δz to mesoscale topographic change. Microscale measurements highlight how Δz varies more pre- to post-event than seasonally or monthly, but regardless of collection type (i.e., seasonal, monthly, or event-based), there was lower Δz in the vegetated areas than in the associated unvegetated and partially vegetated microhabitats. Despite lower Δz values per pin measurement, over the study duration, vegetated pins had a net elevation increase of ≈20 cm, whereas transitional and unvegetated microhabitats had much lower change, near-zero net gain. These results support vegetated microhabitats being more stable and having better sediment retention than unvegetated and transitional areas. Comparatively, mesoscale UAS surfaces typically overestimated Δz, such that variation stemming from vegetation across microhabitats was obscured. However, these data highlight larger mesoscale habitat impacts that cannot be determined from point measurements regarding volumetric change and feature mapping. Changes in features, such as beach access paths, that are associated with increased dynamism are quantifiable using mesoscale remote sensing methods rather than microscale methods. Regardless of the metric, maintaining baseline data is critical for assessing what is captured and missed across spatiotemporal scales and is necessary for understanding the contributors to heterogeneous topographic change in sandy coastal foredunes. Full article

Pearl River Delta (PRD), as one of the most densely populated regions in the world, is facing both natural changes (e.g., sea level rise) and human-induced changes (e.g., dredging for navigation and land reclamation). Bathymetric information is thus important for the protection and management of the estuarine environment, but little effort has been made to comprehensively evaluate the performance of different methods and datasets. In this study, two linear regression models—the linear band model and the log-transformed band ratio model, and two non-linear regression models—the support vector regression model and the random forest regression model—were applied to Landsat 8 (L8) and Sentinel-2 (S2) imagery for bathymetry mapping in 2019 and 2020. Results suggested that a priori area clustering based on spectral features using the K-means algorithm improved estimation accuracy. The random forest regression model performed best, and the three-band combinations outperformed two-band combinations in all models. When the non-linear models were applied with three-band combination (red, green, blue) to L8 and S2 imagery, the Root Mean Square Error (Mean Absolute Error) decreased by 23.10% (35.53%), and the coefficient of determination (Kling-Gupta efficiency) increased by 0.08 (0.09) on average, compared to those using the linear regression models. Despite the differences in spatial resolution and band wavelength, L8 and S2 performed similarly in bathymetry estimation. This study quantified the relative performance of different models and may shed light on the potential combination of multiple data sources for more timely and accurate bathymetry mapping. Full article

In this study, we analyze the influence of the Great East Japan Earthquake, which occurred on 11 March 2011, on the shoreline of the northern Ibaraki Coast. After the earthquake, the area experienced subsidence of approximately 0.4 m. Shoreline changes at eight sandy beaches along the coast are estimated using various satellite images, including the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), ALOS AVNIR-2 (Advanced Land Observing Satellite, Advanced Visible and Near-infrared Radiometer type 2), and Sentinel-2 (a multispectral sensor). Before the earthquake (for the period March 2001–January 2011), even though fluctuations in the shoreline position were observed, shorelines were quite stable, with the averaged change rates in the range of ±1.5 m/year. The shoreline suddenly retreated due to the earthquake by 20–40 m. Generally, the amount of retreat shows a strong correlation with the amount of land subsidence caused by the earthquake, and a moderate correlation with tsunami run-up height. The ground started to uplift gradually after the sudden subsidence, and shoreline positions advanced accordingly. The recovery speed of the beaches varied from +2.6 m/year to +6.6 m/year, depending on the beach conditions. Full article