Search Results (13)

The ocean, covering 71% of Earth’s surface, remains largely unexplored due to the challenges of the marine environment. This study focuses on the Kuźnica Deep in the Baltic Sea, aiming to develop an automatic seabed mapping methodology using multibeam echosounders (MBESs) and machine learning. The research integrates various scientific fields to enhance understanding of the Kuźnica Deep’s underwater landscape, addressing sediment composition, backscatter intensity, and geomorphometric features. Advances in remote sensing, particularly, object-based image analysis (OBIA) and machine learning, have significantly improved geospatial data analysis for underwater landscapes. The study highlights the importance of using a reduced set of relevant features for training models, as identified by the Boruta algorithm, to improve accuracy and robustness. Key geomorphometric features were crucial for seafloor composition mapping, while textural features were less significant. The study found that models with fewer, carefully selected features performed better, reducing overfitting and computational complexity. The findings support hydrographic, ecological, and geological research by providing reliable seabed composition maps and enhancing decision-making and hypothesis generation. Full article

The digital representation of seafloor, a challenge in UNESCO’s Ocean Decade initiative, is essential for sustainable development support and marine environment protection, aligning with the United Nations’ 2030 program goals. Accuracy in seafloor representation can be achieved through remote sensing measurements, including acoustic and laser sources. Ground truth information integration facilitates comprehensive seafloor assessment. The current seafloor mapping paradigm benefits from the object-based image analysis (OBIA) approach, managing high-resolution remote sensing measurements effectively. A critical OBIA step is the segmentation process, with various algorithms available. Recent artificial intelligence advancements have led to AI-powered segmentation algorithms development, like the Segment Anything Model (SAM) by META AI. This paper presents the SAM approach’s first evaluation for seafloor mapping. The benchmark remote sensing dataset refers to Puck Lagoon, Poland and includes measurements from various sources, primarily multibeam echosounders, bathymetric lidar, airborne photogrammetry, and satellite imagery. The SAM algorithm’s performance was evaluated on an affordable workstation equipped with an NVIDIA GPU, enabling CUDA architecture utilization. The growing popularity and demand for AI-based services predict their widespread application in future underwater remote sensing studies, regardless of the measurement technology used (acoustic, laser, or imagery). Applying SAM in Puck Lagoon seafloor mapping may benefit other seafloor mapping studies intending to employ AI technology. Full article

Understanding the dynamics of beach–dune systems is crucial for effective coastal management. The cellular automata model DuBeVeg provides a powerful tool for simulating and understanding the bio-geomorphological evolution of these systems, capturing key interactions of aeolian, hydro-, and vegetation dynamics in a simplified manner. In this study, we present an alternative representation of the aeolian transport component in DuBeVeg, aiming to better capture the saltation transport mode that prevails on beaches. This new representation is compared with the original aeolian transport representation in DuBeVeg, which is inspired by ripple migration. For three beach width scenarios, we considered the effects of the different aeolian transport representations on the predicted foredune morphology after 50 years, as well as the spatio-temporal evolution of the beach–dune system leading to that morphologic state. The saltation transport representation resulted in a more realistic simulation of the seaward expansion of the foredune compared with the original representation, particularly in scenarios with wide and prograding beaches. The new representation also more accurately captured the amplitude of aeolian bedforms emerging across the beach. These findings highlight the importance of selecting the representative transport mode when simulating the transient bio-geomorphological evolution of beach–dune systems. Full article

In this paper, the physiography, geomorphological features, and sedimentary bedforms of the offshore Egadi Islands (Italy) have been illustrated and mapped through an integrated analysis of high-resolution bathymetric, seismo-acoustic, and sedimentological data. The study area is characterized by a wide, up to 25 km, continental shelf which is separated by a NNW-trending linear incision, the Marettimo Channel, along which several erosional and depositional features have been detected and mapped. Sedimentary prograding wedges were detected at water depths between 100–125 m along the shelf margin, which accumulated during the sea-level fall and lowstand stages of the last glacio-eustatic cycle (post- MIS 5.5). This study detected several slope breaks defining scarps across the continental shelf, which were interpreted as coastal cliffs that originated during the post-LGM eustatic sea-level rise. Several fields of different types of sedimentary bedforms, including 2-D and 3-D hydraulic dunes and sorted bedforms, were found across the continental shelf, providing evidence of a high hydrodynamic regime affecting the seafloor. Further on, this study recognized erosive and depositional features related to bottom currents (contourites) in the Marettimo Channel. These findings provide a better understanding of the morpho-sedimentary evolution of the Egadi Islands offshore in the latest Quaternary. Moreover, they offer essential scientific support for effectively managing the most valuable priority habitats for conservation, such as the Posidonia oceanica meadow and coralline algae bioconstructions (Coralligenous habitat). Full article

Short-term changes in shallow bathymetry affect the coastal zone, and therefore their monitoring is an essential task in coastal planning projects. This study provides a novel approach for monitoring shallow bathymetry changes based on drone multispectral imagery. Particularly, we apply a shallow water inversion algorithm on two composite multispectral datasets, being acquired five months apart in a small Mediterranean sandy embayment (Chania, Greece). Initially, we perform radiometric corrections using proprietary software, and following that we combine the bands from standard and multispectral cameras, resulting in a six-band composite image suitable for applying the shallow water inversion algorithm. Bathymetry inversion results showed good correlation and low errors (<0.3 m) with sonar measurements collected with an uncrewed surface vehicle (USV). Bathymetry maps and true-color orthomosaics assist in identifying morphobathymetric features representing crescentic bars with rip channel systems. The temporal bathymetry and true-color data reveal important erosional and depositional patterns, which were developed under the impact of winter storms. Furthermore, bathymetric profiles show that the crescentic bar appears to migrate across and along-shore over the 5-months period. Drone-based multispectral imagery proves to be an important and cost-effective tool for shallow seafloor mapping and monitoring when it is combined with shallow water analytical models. Full article

Aeolian features framed as foredunes worldwide, whose classification faces challenges to separate wave-formed from aeolian ridges, are relevant to the context of anthropic control. An example of this kind of morphology, previously classified as foredunes, is arranged along Brazil’s northeastern coast, and the pertinence of its classification as such or even as truly developed dunes was examined. To contribute to the debate on this issue, detailed geomorphological mapping was carried out through UAV and LIDAR surveys, in addition to the multitemporal study of satellite images and aerial photographs. Ground penetration radar sections, trenches, and particle size analysis were also conducted. Although the obliquity of wind direction to the coastline, this study’s main bedform of focus shows coast-parallel positioning conditioned by the exogenous vegetation previously inserted about 70 m from the high tide line. This morphology showed practically no migration for over 15 years; however, the wind breaks through the vegetation barrier and develops depositional lobes and V-shaped low crests protruding into the mainland. GPR sections reveal cross-strata sets with a high dip angle in only two aeolian sequences, one preceding exogenous vegetation introduction and the other in a contemporary layer, amidst the dominance of horizontal to sub-horizontal strata. The sediments are characteristically aeolian, with cross-strata and morphology resembling incipient protodunes and a few stretches at the lee slope highlighting characteristics of retention or precipitation dunes. There was little similarity to the foredunes compared to the other occurrences along the equatorial northeast coast; there was also an inconsistency in the correlation between the cross-strata and the morphological stage. In addition, the disconnection between the aeolian dynamics and morphogenetic process also differentiates it from regional foredunes. This morphology, therefore, presents aspects that are not characteristic of the classification of foredunes or the naturally formed dunes in the region and thus demands a classification to emphasize the anthropogenic character. Full article

Seabed sedimentary bedforms (SSBs) are strong indicators of current flow (direction and velocity) and can be mapped in high resolution using multibeam echosounders. Many approaches have been designed to automate the classification of such SSBs imaged in multibeam echosounder data. However, these classification systems only apply a geomorphological contextualisation to the data without making direct assertions on the velocities of benthic currents that form these SSBs. Here, we apply an object-based image analysis (OBIA) workflow to derive a geomorphological classification of SSBs in the Moira Mounds area of the Belgica Mound Province, NE Atlantic through k-means clustering. Cold-water coral reefs as sessile filter-feeders benefit from strong currents are often found in close association with sediment wave fields. This OBIA provided the framework to derive SSB wavelength and wave height, these SSB attributes were used as predictor variables for a multiple linear regression to estimate current velocities. Results show a bimodal distribution of current flow directions and current speed. Furthermore, a 5 k-means classification of the SSB geomorphology exhibited an imprinting of current flow consistency which altered throughout the study site due to the interaction of regional, local, and micro scale topographic steering forces. This study is proof-of-concept for an assessment tool applied to vulnerable marine ecosystems but has wider applications for applied seabed appraisals and can inform management and monitoring practice across a variety of spatial and temporal scales. Deriving spatial patterns of hydrodynamic processes from widely available multibeam echosounder maps is pertinent to many avenues of research including scour predictions for offshore structures such as wind turbines, sediment transport modelling, benthic fisheries, e.g., scallops, cable route and pipeline risk assessment and habitat mapping. Full article

Bedforms are key components of Earth surfaces and yet their evaluation typically relies on manual measurements that are challenging to reproduce. Several methods exist to automate their identification and calculate their metrics, but they often exhibit limitations where applied at large scales. This paper presents an innovative workflow for identifying and measuring individual depositional bedforms. The workflow relies on the identification of local minima and maxima that are grouped by neighbourhood analysis and calibrated using curvature. The method was trialed using a synthetic digital elevation model and two bathymetry surveys from Australia’s northwest marine region, resulting in the identification of nearly 2000 bedforms. The comparison of the metrics calculated for each individual feature with manual measurements show differences of less than 10%, indicating the robustness of the workflow. The cross-comparison of the metrics resulted in the definition of several sub-types of bedforms, including sandwaves and palaeoshorelines, that were then correlated with oceanic conditions, further corroborating the validity of the workflow. Results from this study support the idea that the use of automated methods to characterise bedforms should be further developed and that the integration of automated measurements at large scales will support the development of new classification charts that currently rely solely on manual measurements. Full article

Riverbed micro-topographical features, such as crest and trough, flat bed, and scour pit, indicate the evolution of fluvial geomorphology, and have an influence on the stability of underwater structures and overall scour pits. Previous studies on bedform feature extraction have focused mainly on the rhythmic bed surface morphology and have extracted crest and trough, while flat bed and scour pit have been ignored. In this study, to extend the feature description of riverbeds, geomorphic elements mapping was used by employing three geomorphic element classification methods: Wood’s criteria, a self-organization map (SOM) technique, and geomorphons. The results showed that geomorphic element mapping can be controlled by adjusting the slope tolerance and curvature tolerance of Wood’s criteria, using the map unit number and combination of the SOM technique and the flatness of geomorphons. Relatively flat bed can be presented using “plane”, “flat planar”, and “flat” elements, while scour pit can be presented using a “pit” element. A comparison of the difference between parameter settings for landforms and bedforms showed that SOM using 8 or 10 map units is applicable for land and underwater surface and is thus preferentially recommended for use. Furthermore, the use of geomorphons is recommended as the optimal method for characterizing bedform features because it provides a simple element map in the absence of area loss. Full article

The benefits of meadow restoration can be assessed by understanding the connections among geomorphology, hydrology, and vegetation; and multispectral imagery captured from unpiloted aerial systems (UASs) can provide the best method in terms of cost, resolution, and support for vegetation indices. Our field studies were conducted on northern Sierra montane meadows (with ≤70 km² watershed area). The meadows exist in various stages of ecological restoration. Field survey methods included GPS + laser-leveling channel survey, cross-sections, LiDAR, vegetation sampling, soil measurements, and UAS imaging. A sensor captured calibrated blue (465–485 nm), green (550–570 nm), red (663–673 nm), near infrared (NIR) (820–860 nm), and red-edge (712–722 nm) bands at 5.5 cm resolution (as well as thermal at 81 cm resolution) and provided multispectral images and derivative vegetation indices such as the normalized difference vegetation index (NDVI) and red-edge chlorophyll index (Cl_re). This fine-scale imagery extended our morphometric assessment of post-restoration channel bedform patterns and sinuosity related to Carex-influenced soil properties and Salix influence, and also documented groundwater-related effects via Carex patterns evident from spring snowmelt images, as well as NDVI and Cl_re (derived from spring and summer images) in growing to senescent phenological stages. Carex was significantly associated with low bulk density and high soil moisture, NDVI, and Cl_re in low-lying areas, and channel sinuosity was significantly associated with willow influence. Our methods can be applied by restoration managers to assess where projects are threatened by renewed incision and to document levels of carbon sequestration significant to addressing climate change. Full article

An application of the FHyL (field spectral libraries, airborne hyperspectral images and topographic LiDAR) method is presented. It is aimed to map and classify bedforms in submerged beach systems and has been applied to Sabaudia coast (Tirrenyan Sea, Central Italy). The FHyl method allows the integration of geomorphological observations into detailed maps by the multisensory data fusion process from hyperspectral, LiDAR, and in-situ radiometric data. The analysis of the sandy beach classification provides an identification of the variable bedforms by using LiDAR bathymetric Digital Surface Model (DSM) and Bathymetric Position Index (BPI) along the coastal stretch. The nearshore sand bars classification and analysis of the bed form parameters (e.g., depth, slope and convexity/concavity properties) provide excellent results in very shallow waters zones. Thanks to well-established LiDAR and spectroscopic techniques developed under the FHyL approach, remote sensing has the potential to deliver significant quantitative products in coastal areas. The developed method has become the standard for the systematic definition of the operational coastal airborne dataset that must be provided by coastal operational services as input to national downstream services. The methodology is also driving the harmonization procedure of coastal morphological dataset definition at the national scale and results have been used by the authorities to adopt a novel beach management technique. Full article

Spatial distribution and dynamics of intertidal habitats are integral elements of the Wadden Sea ecosystem, essential for the preservation of ecosystem functions and interlocked with geomorphological processes. Protection and monitoring of the Wadden Sea is mandatory and remote sensing is required to survey the extensive, often inaccessible tidal area. Mainly airborne techniques are carried out for decades. High-resolution satellite-borne sensors now enable new possibilities with satellite synthetic aperture radar (SAR) offering high availability of acquisitions during low water time due to independence from daylight and cloud cover. More than 100 TerraSAR-X images from 2009 to 2016 were used to examine the reproduction of intertidal habitats and macrostructures from the flats south of the island of Norderney and comparative areas in the Lower Saxony Wadden Sea. As a non-specific, generic approach to distinguish various and variable surface types continuously influenced by tidal dynamics, visual analysis was chosen which was supported by extensive in situ data. This technically unsophisticated access enabled us to identify mussel beds, fields of shell-detritus, gully structures, mud fields, and bedforms, the latter detected in the upper flats of every East Frisian island. Based on the high frequency of TerraSAR-X recordings for the Norderney area, a bedform shift was observed in a time-series from 2009 to 2015. For the same period, the development of a mud field with an adjoining depression was traced. Beside seasonal variations of the mud field, the formation of a mussel bed settling in the depression was imaged over the years. This study exemplifies the relevance of TerraSAR-X imagery for Wadden Sea remote sensing. Further development of classification methods for current SAR data together with open access availability should contribute to large-scale surveys of intertidal surface structures of geomorphic or biogenic origin and improve monitoring and long-term ecological research in the Wadden Sea and related tidal areas. Full article

In 2017, a detailed study of the Eastern Gulf of Finland (the Baltic Sea) seafloor was performed to identify and map submerged glacial and postglacial geomorphologic features and collect data pertinent to the understanding of sedimentation in postglacial basins. Two key areas within the Gulf were investigate using a multibeam echosounder, SeaBat 8111 and an EdgeTech 3300-HM acoustic sub-bottom profiling system. High-resolution multibeam bathymetric data (3-m resolution) were used to calculate aspect, slope, terrain ruggedness and bathymetric position index using ArcGIS Spatial Analyst and the Benthic Terrain Modeler toolbox. These data and resultant thematic maps revealed, for the first time, such features as streamlined till ridges, end-moraine ridges, and De Geer moraines that are being used for the reconstruction of the deglaciation in the Eastern Gulf of Finland. This deglaciation occurred between 13.8 and 13.3 ka BP (Pandivere–Neva stage) and 12.25 ka BP (Salpausselkä I stage). Interpretations of the seismic-reflection profiles and 3D models showing the surfaces of till, and the identification of the Late Pleistocene sediment and modern bottom relief, indicate deep relative water-level fall in the Early Holocene and, most likely, several water-level fluctuations during this time. Full article