Search Results (128)

The Gulf of Mexico, a geologically complex environment, supports mesophotic coral ecosystems, with reefs such as the Pinnacle Trend, Flower Garden Banks National Marine Sanctuary, the Florida Middle Ground reef system, and Pulley Ridge. Mountain Top Bank is a dome-shaped hardground feature located 60–150 m below the sea surface along the Mississippi–Alabama shelf. It appears to prolong the Pinnacle Trend towards the southeast, bridging the gap between mesophotic coral reefs east and west of the Mississippi Canyon. Shipborne high-resolution multibeam data (bathymetry, backscatter, and water-column) and an AUV photomosaic were collected over the site during several oceanographic expeditions. Data were analyzed and compiled into an ArcGIS geodatabase to produce the first benthic habitat map of Mountain Top Bank. The site is characterized by a network of outcrops and boulders interspersed within a predominately sandy environment. Different seabed features were correlated with the presence and abundance of a diverse array of biota across the phyla of Cnidaria, Porifera, Mollusca, Chordata, Echinodermata, and Rhodophyta. We found the benthic assemblage to be similar to those found at the Pinnacle Trend, supporting the hypothesis that Mountain Top Bank is part of the same reef system and acts as a topographic bridge between ecosystems on the east and west of the Mississippi Canyon. Full article

The accuracy of shallow-water multibeam bathymetry is critically dependent on precise heave correction. However, sensor limitations often lead to incomplete correction, leaving periodic along-track stripe noises (heave residuals) that distort seabed morphology. Traditional filtering methods suppress this noise at the expense of genuine topographic detail. This paper proposes an innovative Data Feedback Correction (DFC) method that corrects the error at its source. DFC establishes a closed-loop framework: it diagnoses the residual’s dominant frequency from central beam data, extracts the residual signal via targeted filtering, and feeds it back as a compensation term into the original sensor heave sequence. This drives a recomputation of the geometric positioning, achieving source-level correction. In a field case, DFC demonstrated targeted, high-fidelity performance. Across all 34 survey lines, DFC achieved an average spectral attenuation of 1.85 dB (range: 1.0–3.7 dB) in the dominant residual band and reduced the RMSE of overlap discrepancies from 0.0923 m to 0.0773 m (a 16.25% improvement). Independent validation using 94,999 control line intersections further demonstrates a 14.31% RMSE improvement relative to an uncorrected control line reference, confirming that the correction improves both internal consistency and external accuracy, significantly enhancing internal consistency. Compared to moving average and wavelet denoising, DFC achieved comparable quantitative improvement while effectively suppressing visual stripes and features that are consistent with the original data, avoiding the over-smoothing or residual noise of traditional methods. This study confirms that closed-loop feedback of data residuals can fundamentally address spectrally aliased stripe noise, shifting the paradigm from “masking noise” to “correcting the source.” The method enhances data consistency in the tested scenario without sacrificing topographic authenticity, providing a promising new tool that warrants further validation across diverse survey conditions. Full article

Seabed studies are a valuable tool in the investigation of active continental margins, both in volcanic and sedimentary settings. Being an example of a slope-confined sedimentary basin, the “Ammontatura” slope basin has been discussed using multibeam bathymetry and seismo-stratigraphic data matched with previously available cores. Being a significant tectonically controlled slope bounded by the Capri-Sorrento regional fault, the southern slope of the Sorrento Peninsula has been explored employing a dense network of bathymetric profiles. The data have shown the underwater extension of the mainland drainage system, comprising a dense network of submarine gullies, reflecting the onshore drainage system. The northern Ischia debris avalanche deposits have been studied through seismo-stratigraphic data, previously unpublished, whose geologic evolution has been placed within the Quaternary stratigraphic framework of Ischia. This research revealed how several geological events, such as the tectonic phases, the emplacement of erosional and depositional domains, the volcanic eruptions, and the reworking of volcanic deposits, interacted in controlling the sedimentary structure of slope basins. In the Ammontatura slope basin, the tectonic setting has probably controlled its emplacement along a NE–SW trending regional fault, resulting from the submarine prolongation of the Sarno-Sebeto normal fault, while intense reworking of volcaniclastic deposits acted as the main control factor in slope settings. Full article

Spain’s extensive marine jurisdiction—comprising a continental shelf of approximately 100,000 km² and an Exclusive Economic Zone approaching one million km²—requires robust geospatial frameworks to support ecosystem assessment and marine policy implementation. This study presents GIS-based methodologies developed by the Spanish Oceanographic Institute (IEO-CSIC) within national initiatives such as LIFE IP INTEMARES project and the implementation of Marine Strategy Framework Directive (European Directive 2008/56/EC). The geospatial workflows developed for these initiatives integrates heterogeneous spatial datasets—such as multibeam bathymetry, acoustic backscatter, Remote Operated Vehicle (ROV) and towed-camera transects, sediment samples, oceanographic profiles, and species-habitat occurrence records—into a unified spatial analysis environment. Applied methods include digital terrain modeling, derivation of geomorphometric indices (e.g., slope, rugosity, curvature), image classification, and spatial statistics to quantify habitat extent, condition, and anthropogenic pressures. An integrated spatial analysis framework combining environmental and anthropogenic data is used to support zoning and management decisions within Marine Protected Areas (MPAs). Additionally, the deployment of WebGIS platforms facilitates data dissemination, iterative review, and stakeholder engagement, thereby enhancing transparency and accessibility. The resulting high-resolution maps, harmonized datasets, and computed spatial indicators—aligned with Marine Strategy Framework Directive (MSFD) descriptors such as habitat distribution (D1C4–C5) and seafloor integrity (D6C2–C3)—demonstrate how GIScience methods provide reproducible, decision-ready information to support the monitoring and management of Spain’s diverse marine ecosystems. Full article

Accurate recognition and segmentation of seafloor topographic units is of great significance for marine surveying and engineering applications. Efficient segmentation of multibeam bathymetric point clouds typically requires projecting them into two-dimensional images. However, segmentation methods based on single-modality images suffer from incomplete information representation and insufficient model adaptability, which often lead to blurred boundaries, false positives, and missed detections, thereby limiting segmentation accuracy. To address these challenges, this study proposes a seafloor topography recognition and segmentation method based on YOLO11n-seg with bimodal image feature fusion, from the perspectives of image generation and model optimization, aiming to improve segmentation accuracy and robustness. First, an early fusion strategy for bimodal images is adopted. Two types of images generated from point clouds via continuous curvature tension spline interpolation are concatenated at the input level, fusing local texture details with absolute water depth information, thereby enhancing the model’s ability to perceive topographic features. Second, a lightweight Efficient Channel Attention (ECA) module is embedded after the Spatial Pyramid Pooling-Fast (SPPF) module of the backbone network. This module adaptively calibrates channel weights, reinforcing the contribution of the grayscale channel to the final segmentation decision. Finally, a weighted BCE-Dice joint loss function is constructed to mitigate class imbalance between flat seabed and topographic regions, while also optimizing boundary segmentation accuracy. Experimental results on a self-constructed multibeam image dataset demonstrate that the proposed method achieves an mAP@50 of 92.8%, representing an absolute improvement of 7.6 percentage points over the baseline model. Notably, the model has only 2.84 M parameters, maintaining a lightweight profile. Full article

This study addresses the challenge of simplifying massive multibeam seafloor topographic point cloud datasets featuring significant spatial heterogeneity. We propose a feature joint entropy-based quantification method for seafloor terrain complexity, which provides a foundation for the adaptive and differentiated simplification of point clouds. In this method, the elevation and slope features of point clouds are treated as two-dimensional random variables that describe terrain morphology; we estimate the Shannon entropy of their joint distribution by constructing a two-dimensional adaptive histogram and use the entropy value to quantify the topographic information content and complexity of local regions. To overcome the parameter sensitivity and subjective dependence inherent in traditional fixed-bin methods, we incorporate the Minimum Description Length (MDL) principle to guide binning optimization, taking the sum of stochastic complexity and model coding length as the evaluation criterion. A dimension-alternating optimization strategy combining dynamic programming and an iterative greedy algorithm is adopted to solve for the optimal binning structure, thus achieving data-driven adaptive binning. To ensure the fairness and reliability of quantification, we adopt a fixed-point number partitioning strategy to decompose the point cloud into several independent analysis nodes and determine the minimum sample size supporting the stable estimation of entropy values through convergence analysis. Experimental results demonstrate that the proposed method, as a consistent and data-driven complexity metric, can reliably reflect the relative complexity of different seafloor terrain regions, thereby providing an objective quantitative basis for subsequent differentiated point cloud simplification. Full article

Submarine canyon-channel systems play a critical role as potential conduits for warm-water upwelling around Antarctica, potentially influencing ice-sheet stability. Integrating multibeam bathymetry, seismic profiles, and morphometric analysis, this study identifies 29 canyon-channel systems along the Adélie Land margin and reveals clear morphological contrasts between the Adélie Depression and the Adélie Bank. Systems in the Depression are elongated, slightly sinuous, and dendritic, with downstream increases in width-to-depth ratio, whereas those on the Bank are shorter, isolated, and single-branched, with irregular along-thalweg variations. Mann–Whitney U tests show significant differences in sinuosity and thalweg gradient (p < 0.01). These contrasts reflect the combined effects of shelf-slope topography, sediment supply, and ice-sheet dynamics. In the Depression, steep slopes, focused glacial sediment input from the Wilkes Subglacial Basin, and associated progradational wedges and mass transport deposits promote mass failures and turbidity-current incision. Strong correlations among canyon-channel length, width, and depth indicate coherent scaling under concentrated sediment supply. In contrast, gentler slopes and lower sediment input on the Bank produce simpler systems. These results highlight how glaciated-margin canyon morphology records coupled sedimentary and ice-sheet–ocean processes. Full article

The Gulf of Taranto (Ionian Sea) is a key transitional sector between the Southern Apennines collisional belt and the Calabrian Arc system, where the expression of Pleistocene–Holocene deformation in the shallow stratigraphic record remains debated. This study focuses on the Taranto Canyon area, the main morphologic feature of the northeastern Gulf of Taranto slope. We integrate high-resolution multibeam bathymetry (10 m grid) with Sparker seismic profiles to (i) define the shallow seismo-stratigraphic framework and (ii) document spatial relationships between shallow discontinuities, morphostructural lineaments, and submarine channel network organization. A simplified tie to the Livia 001 well constrains the subdivision of the shallow succession into four seismic units: the late Pleistocene–Holocene unit (PtH), the Santerno Formation (SNT), the Calcarenite di Gravina (GRA), and the Cupello Limestones (CPL). The PtH interval shows the strongest lateral variability and includes widespread acoustically disturbed bodies and recurrent sub-vertical fluid escape acoustic anomalies. Steep discontinuities producing reflector terminations, minor vertical separation, and localized bending affect PtH and, locally, SNT, with normal fault geometries prevailing where resolvable. Bathymetric mapping reveals multiple lineament families and preferred channel orientations that persist across higher Strahler orders, supporting a structurally conditioned template that guides seafloor morphology, sediment routing, and canyon–slope evolution in the northeastern Gulf of Taranto. Full article

The Taranto Landslide Complex (TLC) is a multi-episode submarine mass-failure system developed along the Apulian continental margin (Gulf of Taranto, northern Ionian Sea) between ~200 and ~900 m water depth. High-resolution multibeam bathymetry and chirp seismostratigraphy were integrated to map five partially overlapping Quaternary mass transport deposits (MTD1–MTD5) and quantify their geometry, conservative volumes, and first-order kinematics. Consistent morphometric parameters indicate mobilities (H/L) and angles of reach typical of continental-slope failures, whereas conservative volumes range between ~0.02–0.35 km³. A depth-averaged sliding-block approach yields bounds on peak velocity and travel time compatible with rapid emplacement. Cross-cutting relationships and post-failure sediment drapes constrain two principal phases of slope instability, expressed as time windows rather than fixed ages. This study develops a framework that integrates uniform morphometric, volumetric, and kinematic features with seismostratigraphy to reconstruct the evolution and relative mobility of multi-episode submarine landslide complexes. The proposed workflow provides a transferable framework for preliminary geohazard assessment on continental margins where repeated slope failure interacts with tectonic and sedimentary forcing. Full article

The multibeam echo sounder (MBES) is a key tool for acquiring high-precision seabed topographic data. However, measurement gaps resulting from its swath-based measurement mode are prevalent, severely compromising the completeness of seabed terrain modeling. To address this issue, this study first categorizes multibeam data gaps into two data degradation patterns with clear hydrographic survey backgrounds: “random degradation” and “rule-based degradation.” Based on this categorization, a highly realistic training dataset that closely matches actual conditions is constructed. To improve the reconstruction accuracy and topographic fidelity, a novel multibeam echo sounder data reconstruction model, the MBES-DDPM, is proposed. Based on the denoising diffusion probabilistic model (DDPM) framework, this model innovatively incorporates gravity anomaly data as prior knowledge. Then, with a designed multisource data fusion guidance mechanism, macro-topographic structural constraints are injected during the diffusion process. Furthermore, a targeted quantitative and qualitative evaluation system is established. The experimental results show that compared with the baseline methods, the MBES-DDPM achieves the best performance across various complex scenarios. Its restored results exhibit an average reduction in root mean square error of at least 34.21% and an average increase in peak signal-to-noise ratio of more than 3.71 dB. Furthermore, it achieves the highest reconstruction fidelity in teams of the terrain slope accuracy metrics. Thus, this research provides a new and reliable solution for accurately restoring large-scale MBES data. Full article

With the rapid development and widespread application of multibeam echo-sounding systems, large-scale and high-resolution seafloor topography can be efficiently acquired, enabling precise mapping of seabed terrain. However, due to complex oceanographic conditions, instrumental noise, and acoustic interferences, the acquired multibeam data often contain outliers that deviate from the true seafloor surface. These outliers can distort the representation of seafloor topography, adversely affecting subsequent geological analysis and engineering applications. To address this issue, a hybrid outlier detection method combining CUBE filtering with the Isolation Forest (IForest) algorithm, termed CUBE-IForest, is proposed. The method first employs CUBE filtering to remove gross outliers based on local uncertainty estimation, followed by the application of IForest to identify subtle anomalies in the refined data, achieving hierarchical detection of outliers. Experimental results based on in situ multibeam bathymetric data from the northeastern Pacific demonstrate that compared with traditional filtering methods the CUBE-IForest approach significantly improves detection accuracy and reduces both false positive and false negative rates by approximately 30%, confirming its efficiency and reliability in seafloor mapping and analysis. Full article

Accurate nearshore bathymetry is essential for various marine applications, including navigation, resource management, and the protection of coastal ecosystems and the services they provide. This study presents an approach to enhance the accuracy of bathymetric estimates derived from high-spatial- and high-temporal-resolution optical satellite imagery. The proposed technique is particularly suited for multispectral sensors that acquire spectral bands sequentially rather than simultaneously. PlanetScope SuperDove imagery was employed and validated against bathymetric data collected using a multibeam echosounder. The study area is the Gulf of Sciacca, located along the southwestern coast of Sicily in the Mediterranean Sea. Here, multibeam data were acquired along transects that are subparallel to the shoreline, covering depths ranging from approximately 7 m to 50 m. Satellite imagery was radiometrically and atmospherically corrected and then processed using a simplified radiative transfer transformation to generate a continuous bathymetric map extending over the entire gulf. The resulting satellite-derived bathymetry achieved reliable accuracy between approximately 5 m and 25 m depth. Beyond these limits, excessive signal attenuation for higher depths and increased water turbidity close to shore introduced significant uncertainties. The innovative aspect of this approach lies in the combined use of spectral averaging among the most water-penetrating bands, temporal averaging across multiple acquisitions, and a liquid-facets noise reduction technique. The integration of these multi-layer inputs led to improved accuracy compared to using single-date or single-band imagery alone. Results show a strong correlation between the satellite-derived bathymetry and multibeam measurements over sandy substrates, with an estimated error of ±6% at a 95% confidence interval. Some discrepancies, however, were observed in the presence of mixed pixels (e.g., submerged vegetation or rocky substrates) or surface artifacts. Full article

Precise lagoon bathymetry remains scarcely available for most tropical islands despite its importance for navigation, resource assessment, spatial planning, and numerical hydrodynamic modeling. Hydrodynamic models are increasingly used for instance to understand the ecological connectivity between marine populations of interest. Island remoteness and shallow waters complicate in situ bathymetric surveys, which are substantially costly. A multisource strategy using historical point sounding, multibeam surveys and well calibrated satellite-derived bathymetry (SDB) can offer the possibility to map entirely extensive and geomorphologically complex lagoons. The process is illustrated here for the rugose complex lagoon of Gambier Islands in French Polynesia. The targeted bathymetry product was designed to be used in priority for numerical larval dispersal modeling at 100 m spatial resolution. Spatial gaps in in situ data were filed with Sentinel-2 satellite images processed with the Iterative Multi-Band Ratio method that provided an accurate bathymetric model (1.42 m Mean Absolute Error in the 0–15 m depth range). Processing was optimized here, considering the specifications and the constraints related to the targeted hydrodynamic modeling application. In the near future, a similar product, possibly at higher spatial resolution, could improve spatial planning zoning scenarios and resource-restocking programs. For tropical island countries and for French Polynesia, in particular, the needs for lagoon hydrodynamic models remain high and solutions could benefit from such multisource coverage to fill the bathymetry gaps. Full article

Pockmarks are ubiquitous seafloor depressions formed by the fluid/gas seepage through marine sediments, with implications for geohazards, benthic ecosystems, and climate-related processes. Despite extensive research, the mechanisms controlling the formation and spatial distribution of pockmarks are not completely understood, owing to the diverse and site-specific geo-environmental conditions. In this study, we provide a first review of over 7500 pockmarks mapped across the Mediterranean and Black seas, showing their relationship with depth range, slope gradient, seafloor lithology, proximity to tectonic faults, and sediment thickness. Our analysis reveals that pockmarks are predominantly located at intermediate water depths (100–700 m), with two main clusters around 100–200 and 500–700 m. They are commonly found on gently sloping seafloor (<4°), often clustering around slope breaks. In detail, two slope-related peaks around 1.5° and 3.5° suggest distinct geological settings for pockmark formation: sediment-rich and low-energy environments versus more dynamic slope domains. Fault proximity plays a critical role, with over 40% of pockmarks occurring within 1 km of mapped faults, indicating that structural discontinuities act as preferential fluid pathways. Pockmarks concentrate in areas with moderate Plio-Quaternary sediment thickness (300–600 m), suggesting an optimal window for overpressure generation and fluid expulsion. A strong lithological control is evident: 74% of pockmarks occur on muddy sand or sand-rich substrates. In terms of ongoing to recent seepage/activity, ~27% of pockmarks show evidence of ongoing fluid seepage (e.g., acoustic gas flares, seismic wipeouts), particularly in regions such as the Black Sea, Aegean, and Central Tyrrhenian, where faulting, salt tectonics, or hydrothermal systems enhance permeability. Conversely, pockmarks in the Western Mediterranean appear to be generally inactive and buried. These findings underscore the influence of tectono-sedimentary architecture on seafloor fluid escape and provide essential insight into methane seepage, slope stability, and benthic habitats. This pedagogic review enhances our understanding of pockmark systems and establishes a foundation for future geohazard assessment, climate studies, and marine resource exploration. Full article

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring. Full article