Search Results (276)

The coastal developments in the Middle East put low priority on tsunami risk assessment due to the rare occurrence and absence of genuine tsunami track records on the coastline in the past. Tsunami-vulnerable coasts, including the east coast of the UAE, need to prepare for, and pay attention to, the impact of future tsunamis due to increased earthquake activity in the region. This study investigated the tsunami characteristics of the nearshore from hypothetical tsunami conditions by applications of numerical modeling and Artificial Neural Network (ANN) methods. The modeling results showed that the maximum tsunami depth at the shore was highest in Khor Fakkan and Mirbih for the given tsunami boundary conditions, while the tsunami withdrawal was greater on the southern bathymetry compared to that on the northern bathymetry when the tsunami period increased. ANN results confirmed that the still sea depth and seabed slope were more important than the tsunami period when predicting the maximum tsunami depth at the shore. Full article

Coastal erosion, exacerbated by climate change, poses a critical global threat to both the environment and human livelihoods. Acquiring accurate, high-resolution topo-bathymetric data is vital for understanding these dynamic environments, without underestimating the hydrodynamic and meteo-oceanographic conditions. However, traditional methods often present significant challenges in achieving comprehensive, high-resolution topo-bathymetric coverage efficiently in shallow coastal zones, leading to a notable ”white ribbon” data gap. This study introduces a novel, integrated methodology combining unmanned aerial vehicles (UAVs) for terrestrial surveys, unmanned surface vehicles (USVs) for bathymetry, and the Global Navigation Satellite System (GNSS) for ground control and intertidal gap-filling. Through this technologically rigorous approach, a seamless Bathymetry-Topography Digital Surface Model for the Guardamar del Segura dune system (Spain) was successfully elaborated using a DJI Mini 2 UAV, Leica Zeno FLX100 GNSS, and Apache 3 USV. The method demonstrated a substantial time reduction of at least 50–75% for comparable high-resolution coverage, efficiently completing the 86.4 ha field campaign in approximately 4 h. This integrated approach offers an accessible and highly efficient solution for generating detailed coastal elevation models crucial for coastal management and research. Full article

Accurate coastal bathymetry is critical for navigation, environmental monitoring, and marine resource management. This study presents a deep learning-based approach that fuses Sentinel-2 multispectral imagery with airborne hyperspectral-derived reference data to generate high-resolution satellite-derived bathymetry (SDB). To address the spatial resolution mismatch between Sentinel-2 (10 m) and LiDAR reference data (1 m), three interpolation methods—Inverse Distance Weighting (IDW), Natural Neighbor (NN), and Spline—were employed to resample spectral reflectance data to a 1 m grid. Two spectral input configurations were evaluated: the log-ratio of Bands 2 and 3, and raw RGB composite reflectance (Bands 2, 3, and 4). A Fully Convolutional Neural Network (FCNN) was trained under each configuration and validated using LiDAR-based depth. The RGB + NN combination yielded the best performance, achieving an RMSE of 1.2320 m, MAE of 0.9381 m, bias of +0.0315 m, and R² of 0.6261, while the log-ratio + IDW configuration showed lower accuracy. Visual and statistical analyses confirmed the advantage of the RGB + NN approach in preserving spatial continuity and spectral-depth relationships. This study demonstrates that both interpolation strategy and input configuration critically affect SDB model accuracy and generalizability. The integration of spatially adaptive interpolation with airborne hyperspectral reference data represents a scalable and efficient solution for high-resolution coastal bathymetry mapping. Full article

Satellite-derived bathymetry (SDB) enables the efficient mapping of shallow waters such as coastal zones but typically requires extensive local ground truth data to achieve high accuracy. This study evaluates the effectiveness of transfer learning in reducing this requirement while keeping estimation accuracy at acceptable levels by adapting a deep learning model pretrained on data from Puck Lagoon (Poland) to a new coastal site in Agia Napa (Cyprus). Leveraging the open MagicBathyNet benchmark dataset and a lightweight U-Net architecture, three scenarios were studied and compared: direct inference to Cyprus, site-specific training in Cyprus, and fine-tuning from Poland to Cyprus with incrementally larger subsets of training data. Results demonstrate that fine-tuning with 15 samples reduces RMSE by over 50% relative to the direct inference baseline. In addition, the domain adaptation approach using 15 samples shows comparable performance to the site-specific model trained on all available data in Cyprus. Depth-stratified error analysis and paired statistical tests confirm that around 15 samples represent a practical lower bound for stable SDB, according to the MagicBathyNet benchmark. The findings of this work provide quantitative evidence on the effectiveness of deploying data-efficient SDB pipelines in settings of limited in situ surveys, as well as a practical lower bound for clear and shallow coastal waters. Full article

This study presents a comprehensive coastal vulnerability assessment framework by integrating a range of physical, environmental, and climatic parameters. Key criteria include shoreline changes, coastal geomorphology, slope, elevation, bathymetry, tidal range, wave height, shoreline change rates, population density, land use and land cover (LULC), temperature, precipitation, and coastal inundation factors. By synthesizing these parameters with real-time coastal monitoring data, the framework enhances the accuracy of regional risk evaluations. The study employs Multi-Criteria Spatial Analysis (MCSA) to systematically assess and prioritize vulnerability indicators, enabling a data-driven and objective approach to coastal zone management. The findings aim to support coastal planners, policymakers, and stakeholders in designing effective, sustainable adaptation and mitigation strategies for regions most at risk. This integrative approach not only strengthens the scientific understanding of coastal vulnerabilities but also serves as a valuable tool for informed decision-making under changing climate and socioeconomic conditions. Full article

Nearshore bathymetry is key to most oceanographic studies and coastal engineering works. This work proposes a new methodology to assess nearshore wave celerity and infer bathymetry from video images. Shoaling and breaking wave patterns were detected on the Timestacks distinctly, and wave celerity was estimated from wave trajectories. The wave type separation enabled the implementation of specific domain formulations for depth inversion: linear for shoaling and non-linear for breaking waves. The technique was validated over a rocky bottom using video acquisition of an online streaming webcam for a period of two days, with significant wave heights varying between 1.7 m and 3.5 m. The results were corroborated in comparison to ground-truth data available up to a depth of 10 m, yielding a mean bias of 0.05 m and a mean root mean square error (RMSE) of 0.43 m. In particular, RMSE was lower than 15% in the outer surf zone, where breaking processes occur. Overall, the depth-normalized RMSE was always lower than 20%, with the major inaccuracy due to some local depressions, which were not resolved. The developed technique can be readily applied to images collected by coastal monitoring stations worldwide and is applicable to drone video acquisitions. Full article

A FEM model of Shallow Wave Equations (SWE-FEM) is studied, taking into account the variable bathymetry of semi-enclosed sea basins. The model, with a spatially varying Coriolis term, is implemented for the description of combined refraction–diffraction effects, from which the eigenperiods and eigenmodes of extended geographical sea areas are calculated by means of a low-order FEM scheme. The model is applied to the western Mediterranean basin, illustrating its versatility to easily include the effects of geographical characteristics like islands and other coastal features. The calculated resonant frequencies and modes depend on the domain size and characteristics as well as the location of the open sea boundary, and it is shown to provide results compatible with tide measurements at several stations in the coastal region of France. The calculation of the natural oscillation modes in the western Mediterranean basin, bounded by open boundaries at the Strait of Gibraltar and the Strait of Sicily, reveals a natural period of around 6 h corresponding to the quarter-diurnal tidal components, which are stationary and of roughly constant amplitude on the northern coast of the basin and on the west coast of Corsica (France). On the east coast of Corsica, on the other hand, these components are of very low amplitude and in phase opposition. The semi-diurnal tidal components observed on the same tide gauges north of the basin and west of Corsica are also quasi-stationary although they are not resonant. Resonant oscillations are also observed at lower periods, especially at a period of around 3 h at the Sète station. This period corresponds to a higher-order natural mode of the western Mediterranean basin, but this resonance seems to be essentially linked to the presence of the Gulf of Lion, whose shallowness and the width of the shelf at this point induce a resonance. Other oscillations are also observed at lower periods (T = 1.5 h at station Fos-sur-Mer, T = 45 min in the Toulon harbour station), due to more local forcing. Full article

In airborne LiDAR measurements of shallow water bathymetry, conventional data processing often overlooks the radiative losses associated with multiple scattering events, affecting detection accuracy. This study presents a Monte Carlo-based approach to construct a mathematical model that accurately characterizes the multiple returns in airborne laser bathymetric systems. The model enables rapid simulation of laser propagation through water, accounting for multiple scattering events. Based on the Beer–Lambert law and incorporating the parameters of typical Jerlov 1 clear coastal water, the proposed model achieves a seamless integration of the H-G phase function with a Monte Carlo random process, enabling accurate simulation and validation of pulse temporal broadening in waters with varying optical transparency. Unlike most existing studies, which primarily focus on modeling the laser emission process, this work introduces a novel perspective by analyzing the probability of light reception in LiDAR return signals, offering a more comprehensive understanding of signal attenuation and detection performance in underwater environments. The results demonstrate that, for detecting underwater targets at depths of 10 m, considering three or more scattering events improves the accuracy by ~7%. For detecting underwater targets at depths of 50 m, considering three or more scattering events improves the accuracy by 15~33%. These findings can help enhance the detection accuracy and efficiency of experimental systems. Full article

The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) employs a photon-counting detection mode with a 532 nm laser to obtain high-precision Earth surface elevation data and offers a new remote sensing method for nearshore bathymetry. The key issues in using ATLAS ATL03 data for bathymetry are achieving automatic and accurate extraction of signal photons in different water environments. Especially for areas with sharply fluctuating topography, the interaction of various impacts, such as topographic fluctuations, sea waves, and laser pulse direction, can result in a sharp change in photon density and distribution at the seafloor, which can cause the signal photon detection at the seafloor to be misinterpreted or omitted during analysis. Therefore, an improved size and direction adaptive filtering (ISDAF) method was proposed for nearshore bathymetry using ATLAS ATL03 data. This method can accurately distinguish between the original photons located above the sea surface, on the sea surface, and the seafloor. The size and direction of the elliptical density filter kernel automatically adapt to the sharp fluctuations in topography and changes in water depth, ensuring precise extraction of signal photons from both the sea surface and the seafloor. To evaluate the precision and reliability of the ISDAF, ATLAS ATL03 data from different water environments and seafloor terrains were used to perform bathymetric experiments. Airborne LiDAR bathymetry (ALB) data were also used to validate the bathymetric accuracy and reliability. The experimental findings show that the ISDAF consistently exhibits effectiveness in detecting and retrieving signal photons, regardless of whether the seafloor terrain is stable or dynamic. After applying refraction correction, the high accuracy of bathymetry was evidenced by a strong coefficient of determination (R²) and a low root mean square error (RMSE) between the ICESat-2 bathymetry data and ALB data. This research offers a promising approach to advancing remote sensing technologies for precise nearshore bathymetric mapping, with implications for coastal monitoring, marine ecology, and resource management. Full article

The demand for maritime–coastal tourism has been intensifying, but its offerings are sometimes limited to a few activities. Some of these activities do not require specific skills or certifications, while others do. This study aimed to investigate what type of activities are carried out by tourism and recreational vessels in the coastal area of the central Algarve (Portugal). To this end, data from the automatic identification system (AIS) of recreational vessels was used to monitor and categorise these activities in a non-intrusive manner. A model (TORMA) was defined to facilitate the analysis of AIS data and relate them to five independent variables (distance from the coast, boat speed, bathymetry, seabed type, and number of pings). The results of the analysis of more than 11 thousand hourly AIS records for passenger, sailing, and charter vessels showed that the 14 most regular ones had strong seasonal patterns, greater intensity in summer, and spatial patterns with more records near some coastal cliffs. This study provides valuable information on the management of motorised nautical activities near the coast and at sea, contributing to more informed and effective tourism regulation and planning. Full article

Coastal habitats are crucial in mitigating the impact of coastal hazards on society. However, the shortage of information about the role of these habitats in reducing floods in Rivers State, Nigeria, is limited. This study aims to assess the contribution of mangrove habitats in protecting coastal communities from flooding using the InVEST coastal vulnerability model (version 3.10.2). The model analyzes various data inputs and assigns relative numbers, ranging from 1 to 5, indicating different levels of exposure. Data on population, bathymetry, shoreline type, land use land cover, and continental shelf were obtained from relevant websites and the InVEST model package. The findings indicate that the mangrove habitats in Rivers State offer minimal protection against coastal flooding due to their degraded state caused by oil spills and over-exploitation. Additionally, sandy beaches provide little to no protection, and the socio-economic conditions in the communities contribute to increased vulnerability to flooding. The study recommends awareness programs to educate the public about the importance of mangroves for coastal protection in addition to their conservation and restoration. Full article

As China’s largest peninsula, the Shandong Peninsula faces recurrent threats from both tropical and extratropical cyclone-induced storm surges. Understanding the distinct mechanisms governing these surge types is critical for developing targeted coastal hazard mitigation strategies. This investigation employs the FVCOM-SWAVE coupled wave–current model to conduct numerical simulations and comparative analyses of two 2022 surge events, Typhoon Muifa (tropical) and the “221003” extratropical surge. The results demonstrate that hydrodynamic responses exhibit strong dependence on surge-generating meteorological regimes. Tropical surge dynamics correlate closely with typhoon track geometry, intensity gradients, and asymmetric wind field structures, manifesting rightward-biased energy intensification relative to storm motion. Conversely, extratropical surge variations align with evolving wind-pressure configurations during cold air advection, driven by synoptic-scale atmospheric reorganization. The hydrodynamic environmental response in the sea areas surrounding Jiaodong and Laizhou Bay is particularly pronounced, influenced by the intensity of wind stress on the sea surface, as well as the bathymetry and coastal geometry. Full article

In recent years, Kazakhstan has faced the problem of sustainable development in the field of operation of a number of reservoirs: periods of drought lead to a systematic decrease in accumulated fresh water reserves, and the flood of 2024 led to the flooding of a number of settlements. The article raises questions about the real state of the region’s reservoirs (using the example of the Karatomar reservoir), the accuracy of the conducted bathymetric studies, and the correctness of estimating the required step (or distance between the control points being taken) of the tacks (trajectory lines) of the measurement, which was carried out using the Apache 3 bathymetric drone. The study of the patterns of modeling accuracy from the frequency of tacks (trajectory lines) was carried out using kriging methods. Reservoir models were built in QGis and Surfe. When analyzing the coastline, Sentinel-2 space images and Kazvodkhoz (Kazakhstani state enterprise) data were used. The result of the study was an algorithm for determining the step of tacks (trajectory lines) for modern bottom geomorphology. The conducted research has shown that over 78 years of use, the reservoir’s parameters have undergone significant changes. A similar situation of significant deterioration in parameters is characteristic of other hydrotechnical structures in the region. Full article

Coastal areas have been the target of interdisciplinary research aiming to support studies related to their socio-economic and ecological value and their role in protecting backshore ecosystems and assets from coastal erosion and flooding. Some of these studies focus on either onshore or inshore areas using sensors and collecting valuable information that remains unknown and untapped by other researchers. This research demonstrates how satellite, aerial, terrestrial and marine remote sensing techniques can be integrated and inter-validated to produce accurate information, bridging methodologies with different scope. High-resolution data from Unmanned Aerial Vehicle (UAV) data and multispectral satellite imagery, capturing the onshore environment, were utilized to extract underwater information in Coral Bay (Cyprus). These data were systematically integrated with hydroacoustic including bathymetric and side scan sonar measurements as well as ground-truthing methods such as drop camera surveys and sample collection. Onshore, digital elevation models derived from UAV observations revealed significant elevation and shoreline changes over a one-year period, demonstrating clear evidence of beach modifications and highlighting coastal zone dynamics. Temporal comparisons and cross-section analyses displayed elevation variations reaching up to 0.60 m. Terrestrial laser scanning along a restricted sea cliff at the edge of the beach captured fine-scale geomorphological changes that arise considerations for the stability of residential properties at the top of the cliff. Bathymetric estimations derived from PlanetScope and Sentinel 2 imagery returned accuracies ranging from 0.92 to 1.52 m, whilst UAV reached 1.02 m. Habitat classification revealed diverse substrates, providing detailed geoinformation on the existing sediment type distribution. UAV data achieved 89% accuracy in habitat mapping, outperforming the 83% accuracy of satellite imagery and underscoring the value of high-resolution remote sensing for fine-scale assessments. This study emphasizes the necessity of extracting and integrating information from all available sensors for a complete geomorphological and marine habitat mapping that would support sustainable coastal management strategies. Full article

Sediment transportation on coasts can be significantly affected by rivers, wave–wind effects, and human activities. As a result, undesirable effects such as shoaling or erosion may occur in fishery shelters. This study examines the “Sandıktaş a Fishery Shelter”, a coastal structure in the Eastern Black Sea region of Turkey, and its susceptibility to shoaling. Bathymetric measurements were performed within the nearshore and onshore, and sediment samples were taken periodically from selected points and analyzed in the laboratory. The characteristic grain diameters of the sedimentation were obtained. It was revealed that the average grain diameter was d₅₀ = 0.30–0.91, caused by an increase of 11,611 m³ in shoaling, which caused the decrease of 8 cm water depth that occurred between 2019 and 2022. The entrance of the fishery shelter has become progressively shallower, making it difficult for boats to navigate. Existing breakwater configurations played a role in trapping sediments, requiring optimized breakwater designs/modifications for improved sediment control. The Mann–Kendall test showed an increasing trend in sediment accumulation, particularly in coarser fractions. The findings highlight the necessity of periodic dredging and potential structural modifications to mitigate shoaling and ensure the long-term sustainability of the fishery shelter. Moreover, they emphasize the critical challenges caused by sedimentation in fishery shelters and provide data-driven recommendations for enhancing coastal engineering practices and maintenance strategies. Full article