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Nowadays, the employment of high-resolution Digital Surface Models (DSMs) and RGB orthophotos has become fundamental in coastal system studies. This work aims to explore the potentiality of low-cost Unmanned Aerial Vehicle (UAV) surveys to monitor the geomorphic and vegetation state of coastal sand dunes by means of high-resolution (2–4 cm) RGB orthophotos and DSMs. The area of study (Punta Marina, Ravenna, Italy), in the North Adriatic Sea, was considered very suitable for these purposes because it involves a residual coastal dune system, damaged by decades of erosion, fragmentation and human intervention. Recently, part of the dune system has been involved in a restoration project aimed at limiting its deterioration. RGB orthophotos have been used to calculate the spectral information of vegetation and bare sand and therefore, to monitor changes in their relative cover area extension over time, through the using of semi-automatic classification algorithms in a GIS environment. Elevation data from high-resolution DSMs were used to identify the principal morphological features: (i) Dune Foot Line (DFL); (ii) Dune Crest Line (DCL); Dune seaward Crest Line (DsCL); Stable Vegetation line (SVL). The USGS tool DSAS was used to monitor dune dynamics, considering every source of error: a stable pattern was observed for the two crest lines (DCL and DsCL), and an advancing one for the others two features (DFL and SVL). Geomorphological data, as well as RGB data, confirmed the effectiveness of planting operations, since a constant and progressive increase of the vegetated cover area and consolidation of the dune system was observed, in a period with no energetic storms. The proposed methodology is rapid, low-cost and easily replicable by coastal managers to quantify the effectiveness of restoration projects. [ABSTRACT FROM AUTHOR]

This work capitalises on the morphodynamic study of a scraped artificial dune built on the sandy beach of Porto Garibaldi (Comacchio, Italy) as a barrier to protect the touristic facilities from sea storms during the winter season and contributes to understanding of the role of elevation data uncertainty and uniform thresholds for change detection (TCDs) on the interpretation of volume change estimations. This application relies on products derived from unmanned aerial vehicle (UAV) surveys and on the evaluation of the uncertainty associated with volume change estimations to interpret the case study morphodynamics under non-extreme sea and wind conditions. The analysis was performed by comparing UAV-derived digital elevation models (DEMs)—root mean squared error (RMSE) vs. global navigation satellite system (GNSS) < 0.05 m—and orthophotos, considering the significance of the identified changes by applying a set of TCDs. In this case, a threshold of ~0.15 m was able to detect most of the morphological variations. The set of TCD ≤ 0.15 m was considered to discuss the significance of minor changes and the uncertainty of volume change calculations. During the analysed period (21 December 2016–20 January 2017), water levels and waves affected the front of the artificial dune by eroding the berm area; winds remodelled the entire dune, moving the loose sand around the dune and further inland; sediment volumes mobilised by sea and wind forcing were comparable. This work suggests that UAV-derived coastal morphological variations should be interpreted by integrating: (i) a set of uniform thresholds to detect significant changes; (ii) the uncertainty generated by the propagation of the original uncertainty of the elevation products; (iii) the characteristics of the morphodynamic drivers evaluated by adopting uncertainty-aware approaches. Thus, the contribution of subtle morphological changes—magnitudes comparable with the instrumental accuracy and/or the assessed propagated uncertainty—can be properly accounted for. [ABSTRACT FROM AUTHOR]

Rubble islands are dynamic sedimentary features present on reef platforms that evolve under a variety of morphodynamic processes and controlling mechanisms. They provide valuable inhabitable land for small island nations, critical habitat for numerous species, and are threatened by climate change. Aiming to investigate the controlling mechanisms dictating the evolution of One Tree Island (OTI), a rubble island in the Southern Great Barrier Reef, we combined different remotely-sensed data across varying timescales with wave data extracted from satellite altimetry and cyclone activity. Our findings show that (1) OTI had expanded by 7% between 1978 and 2019, (2) significant gross planform decadal adjustments were governed by the amount, intensity, proximity, and relative position of cyclones as well as El Niño Southern Oscillation (ENSO) phases, and (3) the mechanisms of island growth involve rubble spits delivering and redistributing rubble to the island through alongshore sediment transport and wave overtopping. Frequent short-term monitoring of the island and further research coupling variations in the different factors driving island change (i.e., sediment availability, reef-wave interactions, and extreme events) are needed to shed light on the future trajectory of OTI and other rubble islands under a climate change scenario. [ABSTRACT FROM AUTHOR]

Unusual shore-normal and barred-like rhythmic features were found in Camposoto Beach (Bay of Cádiz, SW Spain) during a monitoring program using unmanned aerial systems (UAS). They appeared in the backshore and persisted for 6 months (October 2017–March 2018). Their characteristics and possible formation mechanism were investigated analyzing: (1) UAS-derived high-resolution digital elevation models (DEMs), (2) hydrodynamic conditions, and (3) sediment samples. The results revealed that the features did not migrate spatially, that their wavelength was well predicted by the edge wave theory, and that they shared characteristics with both small-scale low-energy finger bars (e.g., geometry/appearance and amplitude) and swash cusps (e.g., wavelength, seaward circulation pattern, and finer and better sorted material in the runnels with respect to the crests). Our findings pinpoint to highly organized swash able to reach the backshore during spring tides under low-energy and accretionary conditions as well as backwash enhanced by conditions of water-saturated sediment. This study demonstrates that rhythmic features can appear under different modalities and beach locations than the ones observed up to date, and that their unusual nature may be attributed to the low spatiotemporal resolution of the traditional coastal surveying methods in comparison with novel technologies such as UAS. [ABSTRACT FROM AUTHOR]

Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat. [ABSTRACT FROM AUTHOR]