Marine Surveys Research Articles

System Theory and Human Factors Hazard Identification Approach for Marine Survey Operation

Abstract Marine survey operation is one of the most frequent and essential activities in enhancing ocean knowledge. Some dangerous tasks and activities involve scientists, marine crews, survey equipment, and sensors, such as deploying equipment near the seabed, collecting the sediment sample, and towing the equipment with the ship’s movement. Since it consists of several controllers and components, the comprehensive system theory must be applied to analyse the risk, and the effect of human error must be incorporated as the equipment’s controller within the system. This study provides a holistic hazard identiMication of marine survey operation by using System Theory Process and Analysis (STPA) and integrating it with the Human Factors ClassiMication System (HFACS) to deMine the unsafe control actions (UCA) and failure scenarios. According to the STPA, 194 UCAs could occur. The main causal factors of the UCAs are human and followed by technical errors. The STPA-HFACS analysis indicated that additional human and equipment actions would have a detrimental effect on the failures of the operation. This study will beneMit stakeholders in marine survey operations with an alternative method for risk analysis.

The green marine waste collector routing optimization with puma selectison-based neighborhood search algorithm

AbstractImproper waste disposal by humans has created significant environmental issues in the marine ecosystem, including endangering aquatic life and accelerating the extinction of certain marine species. Due to the floating nature of the marine debris, the coordinates for collecting activities must be estimated in advance. In this article, GNOME software is used to estimate the coordinates of debris, and then a fleet of several ships is used to collect them. Also, a mixed integer linear programming model is presented for the routing optimization of debris collection fleets. The proposed optimization model formulates the objective function based on numerous factors, including labor cost, rent, and ship insurance, and considers constraints on fuel tank capacity, the time window, and the ship’s cargo capacity. A new hybrid algorithm combining the Puma algorithm and neighborhood search is proposed to address the problem. Metropolis acceptance is used in the simulated annealing algorithm to avoid the local optima and greedy selection. Numerical examples of the marine survey and the port of Rotterdam are used to test the proposed approach, which has been proven effective in several scenarios. Results achieved from the proposed hybrid method demonstrate considerable performance improvement in solving the problem. This approach has decreased total fuel and labor costs by 10–15% compared to conventional methods, with minimized time window violation reaching 25%. These results show a significant reduction in total operational costs with proper scheduling and route planning.

Influence of Ocean Current Features on the Performance of Machine Learning and Dynamic Tracking Methods in Predicting Marine Drifter Trajectories

Accurately and rapidly predicting marine drifter trajectories under conditions of information scarcity is critical for addressing maritime emergencies and conducting marine surveys with resource-limited unmanned vessels. Machine learning-based tracking methods, such as Long Short-Term Memory networks (LSTM), offer a promising approach for trajectory prediction in such scenarios. This study combines satellite observations and idealized simulations to compare the predictive performance of LSTM with a resource-dependent dynamic tracking method (DT). The results indicate that when driven solely by historical drifter paths, LSTM achieves better trajectory predictions when trained and tested on relative trajectory intervals rather than the absolute positions of individual trajectory points. In general, LSTM provides a more accurate geometric pattern of trajectories at the initial stages of forecasting, while DT offers superior accuracy in predicting specific trajectory positions. The velocity and curvature of ocean currents jointly influence the prediction quality of both methods. In regions characterized by active sub-mesoscale dynamics, such as the fast-flowing and meandering Kuroshio Current and Kuroshio Current Extension, DT predicts more reliable trajectory patterns but lacks precision in detailed position estimates compared to LSTM. However, in areas dominated by the fast but relatively straight North Equatorial Current, the performance of the two methods reverses. The two methods also demonstrate different tolerances for noise and sampling intervals. This study establishes a baseline for selecting machine learning methods for marine drifter prediction and highlights the limitations of AI-based predictions under data-scarce and resource-constrained conditions.

Giant landslide, hidden caldera structure, magnetic anomalies and tectonics in southern Tyrrhenian Sea (Italy)

Phlegraean Fields and Ischia Island are large, densely populated, active volcanic structures located in the Campanian Tyrrhenian margin between the onshore and offshore sectors. While the emerged landforms provide significant insights into a series of intense volcano-tectonic events of the last 60 ka, our understanding of the sub-marine portion of these volcanoes remains limited due to its inaccessibility to direct exploration. In the last decades, the use of magnetic methods has proven to be useful in volcanic context, given the presence of large magnetization contrasts, whereas the implementation of a high-resolution Digital Elevation Model (DEM) has allowed the integration of detailed morphological analyses into the geophysical studies. In this work, we present two new high-resolution airborne and shipborne magnetic surveys, carried out by the National Institute of Geophysics and Volcanology (INGV) in the marine sector of the Phlegraean Fields caldera (Pozzuoli Bay) and surrounding sea sectors. Moreover, the new datasets have been integrated with older marine surveys carried out by the National Research Council (CNR) to extend the resulting magnetic anomaly map embracing the whole Campanian offshore volcanic structures, excluding Ischia Island. As a result, we present here three new magnetic anomaly maps used for an integrated interpretation of magnetic, morphological, and tectonic features. The study results provide valuable insights into the relationship between volcanic, magmatic, and tectonic activity, which may be useful for further investigations. Among the most notable findings are: the identification of the magnetic signatures of regional faults, previously unknown caldera structures, and a massive rock avalanche. Consequently, our research provides a significant contribution to seabed exploration aimed at identifying potential hazard factors in the study area.

Marine Characteristic Changes Associated with Typhoon Soulik Observed Using Wave and Underwater Gliders

To assess the impact of Typhoon Soulik on the marine environment, unmanned platforms, specifically wave and underwater gliders, are used for surveys in the East Sea. From August 20 to 30, 2018, the wave glider collected meteorological data, while the underwater glider conducts CTD measurements within the typhoon’s impact zone. The data are compared with marine buoy data from the Korea Meteorological Administration and forecast model outputs using RMSE and correlation coefficients to evaluate the characteristics of each data source. The unmanned platform effectively capture the marine environmental changes during the typhoon passage, and the forecast model results show relatively lower RMSE and correlation with the observed data. The study also determines the time required for conditions to revert to pre-typhoon states. This research demonstrates the potential of unmanned platform data for enhancing marine surveys and forecast model accuracy.

How marine are Marine Stramenopiles (MAST)? A cross-system evaluation.

Marine Stramenopiles (MAST) were first described two decades ago through ribosomal RNA gene (rRNA gene) sequences from marine surveys of microbial eukaryotes. MAST comprise several independent lineages at the base of the Stramenopiles. Despite their prevalence in the ocean, the majority of MAST diversity remains uncultured. Previous studies, mainly in marine environments, have explored MAST's cell morphology, distribution, trophic strategies, and genomics using culturing-independent methods. In comparison, less is known about their presence outside marine habitats. Here, we analyse the extensive EukBank dataset to assess the extent to which MAST can be considered marine protists. Additionally, by incorporating newly available rRNA gene sequences, we update Stramenopiles phylogeny, identifying three novel MAST lineages. Our results indicate that MAST are primarily marine with notable exceptions within MAST-2 and MAST-12, where certain subclades are prevalent in freshwater and soil habitats. In the marine water column, only a few MAST species, particularly within clades -1, -3, -4, and -7, dominate and exhibit clear latitudinal distribution patterns. Overall, the massive sequencing dataset analysed in our study confirms and partially expands the previously described diversity of MASTs groups and underscores the predominantly marine nature of most of these uncultured lineages.

Full Coverage Path Planning for Torpedo-Type AUVs’ Marine Survey Confined in Convex Polygon Area

In this paper, we present a full coverage path planning (CPP) algorithm for the marine surveys conducted in the convex polygon shaped search area. The survey is supposed to carry out by torpedo-type AUVs (autonomous underwater vehicles). Due to their nonholonomic mechanical characteristics, these vehicles have nonzero minimum turning radius. For any given polygon shaped search area, it can always be partitioned into one or more convex polygons. With this in mind, this paper proposes a novel search algorithm called CbSPSA (Calculation based Shortest Path Search Algorithm) for full coverage of any given convex polygon shaped search area. By aligning the search inter-tracks alongside the edge with the minimum height, we can guarantee the minimum number of the vehicle’s turns. In addition, the proposed method can guarantee the planned path is strictly located inside the polygon area without overlapped or crossed path lines, and also has the total path length as short as possible. Considering the vehicle’s nonzero minimum turning radius, we also propose a sort of smoothing algorithm which can smooth the waypoint path searched by CbSPSA so that the vehicle can exactly follow it. The smoothed path is also guaranteed to be strictly located inside the polygon. Numerical simulation analyses are also carried out to verify the effectiveness of the proposed schemes.

Multidimensional Evaluation of Altimetry Marine Gravity Models with Shipborne Gravity Data from a New Platform Marine Gravimeter

With the development of satellite altimetry technology and the application of new altimetry satellites, the accuracy and resolution of altimeter-derived gravity field models have improved over the last decades. Nowadays, they are close enough to shipborne gravimetry. In this paper, multi-source shipborne gravity data in the South China Sea were taken to evaluate the accuracies of two high-precision altimeter-derived marine gravity field models (SS V30.1, DTU17). In these shipborne gravity data, there are dozens of routes’ ship gravimetry data, obtained from the National Geophysical Data Center (NGDC); data were tracked from a marine survey with a commercial marine gravimeter (type KSS31M), and data were tracked from a marine gravimetry campaign that was conducted with a newly developed platform gravimeter (type JMG) in the South China Sea in September 2020. After various data filtering, processing, and calibrations, the shipborne gravity data were validated with crossover points analysis. Then, the processed shipborne data were employed to evaluate the accuracy of the altimeter-derived marine gravity field models. During this procedure, the quality of JMG shipborne gravity data was compared with the results of KSS31M and NGDC data. Analysis and evaluation results show that the crossover points verification accuracies of KSS31M and JMG are 0.70 mGal and 1.61 mGal, which are much better than the accuracy of NGDC, which is larger than 8.0 mGal. In the area where the bathymetry changes slowly, the root mean square error values between altimetry gravity models and KSS31M data are respectively 3.28 mGal and 4.54 mGal, and those of the JMG data are respectively 2.94 mGal and 2.60 mGal. According to the above results, we can conclude that the JMG has the same 1–2 mGal accuracy level as KSS31M and can meet the measurement requirements of marine gravity.

Integrating visual and molecular approaches for fish eggs analysis: A study on formaldehyde fixation and storage procedures

AbstractAccurate taxonomic classification and developmental stage determination of fish eggs are crucial for ecological monitoring, conservation efforts, and stock assessments. Traditional methods for fish and fisheries rely on visual examination of morphological traits, but they face challenges due to species overlap especially for early stages. Molecular tools, such as DNA barcoding, offer higher resolution in taxonomic identification but may not provide developmental stage information. This study explores the effectiveness of different formaldehyde fixation concentrations and storage procedures on fish eggs collected from Lofoten, Norway, for both visual and molecular analysis. Visual analysis successfully identified developmental stage for all fixation solutions. Molecular barcoding using the 16S rRNA gene identified up to 100% of eggs at the species level, with decreasing success rates over time when stored in formaldehyde fixation. The highest DNA barcoding success rates were accomplished using 4% formaldehyde fixation for 12‐ or 24‐h following transfer to ethanol. Using 0.5% and 1% formaldehyde fixation up to 8 weeks also resulted in high DNA success rates, but results deteriorated with increasing storage time. This study provides valuable insights for integrating visual and molecular methods for fish egg analysis, with practical implications for sample preservation during marine surveys.

Authentic fault models and dispersive tsunami simulations for outer-rise normal earthquakes in the southern Kuril Trench

The southern Kuril Trench is one of the most seismically active regions in the world. In this study, marine surveys and observations were performed to construct fault models for possible outer-rise earthquakes. Seismic and seafloor bathymetric surveys indicated that the dip angle of the outer-rise fault was approximately 50°–80°, with a strike that was slightly oblique to the axis of the Kuril Trench. The maximum fault length was estimated to be ~ 260 km. Based on these findings, we proposed 17 fault models, with moment magnitudes ranging from 7.2 to 8.4. To numerically simulate tsunami, we solved two-dimensional dispersive wave and three-dimensional Euler equations using the outer-rise fault models. The results of both simulations yielded identical predictions for tsunami with short-wavelength components, resulting in significant dispersive deformations in the open ocean. We also found that tsunami generated by outer-rise earthquakes were affected by refraction and diffraction because of the source location beyond the trench axis. These findings can improve future predictions of tsunami hazards.Graphical

Кластерный анализ геофизических полей при тектоническом районировании Африкано-Антарктического сектора Южного океана

The tectonic zoning of the African-Antarctic sector of the Southern Ocean was carried out on the basis of cluster analysis of a large volume of heterogeneous geophysical and geological data. It is known that the degree of geological and geophysical exploration of this part of the ocean by marine surveys and drilling remains extremely low. The results of such an analysis make it possible in areas with weak geophysical knowledge to quickly draw up tectonic zoning schemes based on regional geophysical data that are freely available throughout the entire territory of the world ocean and use them as a basis for further interpretation. The following materials were used as input data or classification features: ocean floor topography, gravity anomalies in free air and in the Bouger reduction, ∆Ta anomalous magnetic field model, ocean floor age, geoid height data, and the SL2013sv seismotomography model. «K-means» algorithms and the «Gaussian mixtures» method used for clustering. Based on the results of the application of these algorithms, cluster models of the study region were obtained, in which the selected classes fully reflect the main tectonic elements.

Risk Analysis of Equipment Loss During Marine Survey Operation by Integrating Fault Tree to Bayesian Network

Risk Analysis of Equipment Loss During Marine Survey Operation by Integrating Fault Tree to Bayesian Network

A Study of Multibeam Line Measurement Problems Based on Analytic Geometry and Mechanistic Analysis

Based on the important application of multibeam bathymetric systems in marine science and engineering, this study explores their working principle and application potential. Through the establishment of a mathematical model, problems such as coverage width and distance between survey lines are solved, and an optimized survey line layout scheme is proposed. For the seabed topography data, combined with geometric analysis and visualization technology, accurate measurement and analysis of seabed topography is realized, which provides important support for marine survey, resource exploration and underwater engineering. The research results are of guiding significance for the further development and application of multibeam bathymetry technology and provide strong support for research and practice in related fields.

Construction of line Layout Model Based on Geometric Deduction and Constrained Heuristic Search

Based on problem B of the National Mathematical Contest in Modeling for College Students in 2023, this paper establishes a model through geometric deductive deduction, and establishes and solves an optimal model of survey line layout through constrained heuristic algorithm. In problem 1, a mathematical model of coverage width and overlap rate is established based on triangle relation and triangle sine theorem by finding the mathematical relationship between target quantity and known quantity. In problem 2, the angle between the known direction of the survey line and the projection of the normal direction of the submarine slope on the horizontal plane is . We can imagine a surface perpendicular to the direction of the measurement line, and then find the slope of the imaginary surface according to the geometric relationship, and replace the slope Angle of problem 1 with the imaginary slope Angle to obtain the mathematical model of the coverage width. Based on this, the constraints of the Angle and overlap rate of the line are added, and the problem 3 is simplified into the optimization problem of multiple routes in problem 2. Finally, by changing the parameter setting of slope Angle in the model, the sensitivity analysis is carried out, and it is found that the model is stable and reliable.To sum up, the problems from one to four are gradually deepened and progressively advanced, and the development of Marine survey field is facilitated by establishing a model of depth survey line layout.

Autonomous underwater vehicle link alignment control in unknown environments using reinforcement learning

AbstractHigh‐speed underwater wireless optical communication holds immense promise in ocean monitoring and surveys, providing crucial support for the real‐time sharing of observational data collected by autonomous underwater vehicles (AUVs). However, due to inaccurate target information and external interference in unknown environments, link alignment is challenging and needs to be addressed. In response to these challenges, we propose a reinforcement learning‐based alignment method to control the AUV to establish an optical link and maintain alignment. Our alignment control system utilizes a combination of sensors, including a depth sensor, Doppler velocity log (DVL), gyroscope, ultra‐short baseline device, and acoustic modem. These sensors are used in conjunction with a particle filter to observe the environment and estimate the AUV's state accurately. The soft actor‐critic algorithm is used to train a reinforcement learning‐based controller in a simulated environment to reduce pointing errors and energy consumption in alignment. After experimental validation in simulation, we deployed the controller on an actual AUV called Tri‐TON. In experiments at sea, Tri‐TON maintained the link and angular pointing errors within 1 m and , respectively. Experimental results demonstrate that the proposed alignment control method can establish underwater optical communication between AUV fleets, thus improving the efficiency of marine surveys.

Coupled Inversion of Amplitudes and Traveltimes of Primaries and Multiples for Monochannel Seismic Surveys

Engineers need to know properties of shallow marine sediments to build piers, pipelines and even offshore windfarms. We present a method for estimating the density, P velocity and thickness of these sediments. The traveltime inversion of primary and multiple reflections enables their semiquantitative estimation in marine surveys when using a minimal acquisition system such as a monochannel Boomer. Picking errors, ambient noise and interfering events lead to significant errors in the estimates. Similar, albeit milder, instabilities occur when inverting the signal amplitudes to determine the reflectivity of the layer interfaces. In this paper, we introduce a coupling between the separate inversion of amplitudes and traveltimes to obtain a better Earth model. The P velocity shows up in two stable terms provided by the separate inversions: the acoustic impedance of shallow sediments (through the amplitudes) and the transit time across the sediment layer (through the traveltimes). We couple the two inversion engines by imposing a smoothness condition on velocity and density and thickness of the layer while keeping the impedance and traveltime constant. We thus exploit the ambiguity of the solution to introduce geological criteria and reduce the noise contribution. We validated the proposed method with synthetic and real data.

Use Of The Yamaha F100B Outboard Engine As a Populsion On The Rinca and Bawean Survey Boats

The aim of this research is to determine the use of the Yamaha F100B outboard engine as a propulsion for the Rinca and Bawean survey boats. The research was carried out within one month, namely August to September 2023. This research was carried out using practical field work methods. The variables in this research were the specification,work process, fuel efficiency system, superiority, and environmental impact. The method in this research uses the observation method, namely the method of collecting data by recording directly while in the field. The research results show that the use of a Yamaha F100B outboard motor as a propulsion is able to provide adequate thrust for the survey vessel, with efficient fuel consumption. In the context of survey vessels, the reliability and speed of these motors are important factors in supporting successful marine survey operations.

Bycatch and pollution are the main threats for Burmeister's porpoises inhabiting a high-industrialized bay in the Humboldt Current System

Pollution and bycatch are two of the main threats for cetaceans worldwide. These threats are exacerbated for nearshore species particularly for those in regions with intense industrial and fishing activities. Burmeister's porpoise is endemic to South America, has a Near Threatened conservation status because of long-term mortality in fisheries. Burmeister's porpoise occur in Mejillones Bay, northern Chile, a hot spot for heavy metals pollution from the mining industry and an intense industrial and artisanal purse-seine fishing area. From 2018 to 2021, we conducted systematic marine surveys to assess the abundance, distribution and habitat use of Burmeister's porpoises. We responded to stranding reports from 2018 to 2022, and necropsied nine individuals. From five of these, we analyzed the metal concentrations (As, Cd, Cr, Cu, Pb, Hg, Se and Zn) in muscle and skin tissues. Results showed an abundance of 76.17 individuals (CV = 25.9%) and an average density of 0.45 individuals/km2 (CV = 26%). Burmeister's porpoises were observed year round, 22.2% were mother-calf pairs present in austral summer at an average of 90.6 m depth in the southwestern bound of the bay. Two-thirds of stranded specimens died due to bycatch and one died due to bottlenose dolphin (Tursiops truncatus) attack. We report a dead Burmeister's porpoise positive for avian flu virus A (H5N1). Metals analyzed were found in muscle and skin tissues of stranded Burmeister's porpoises in the following order (Zn > Cu > Cr > As > Hg > Pb > Cd). Although we could not assess pollution as a cause of mortality, Cr, As and Pb concentrations exceeded the concentrations found in other porpoises species worldwide. We conclude that bycatch and pollution as the main threats for Burmeister's porpoise survival in northern Chile. Future studies should investigate the use of acoustic deterrent alarms to mitigate the bycatch in the bay and consider the Burmeister's porpoise as a sentinel species of pollution in northern Chilean coast.

Unveiling Underwater Structures: MobileNet vs. EfficientNet in Sonar Image Detection

Deep learning techniques have led to an increased use of Convolutional Neural Networks (CNN) in recognizing images for marine surveys and classifying underwater objects. Applying CNN for the automatic identification of targets in side-scan sonar (SSS) images can boost accuracy and efficiency. Using transfer learning and deep learning as lenses, this work explores the field of underwater item detection. Comparing performance of MobileNet and EfficientNet in performing the task of underwater item classification from sonar images is the central research objective of this study. These two well-known convolutional neural networks were the subject of a thorough investigation to help explain this. In order to fine-tune pre-trained models on a dataset of sonar images, the study approach used the transfer learning technique. We conducted tests on MobileNet and EfficientNet and thoroughly assessed each of their accuracy levels. This study has two main conclusions. First, showing promise as a strong model for underwater object identification, EfficientNet performed exceptionally well in the classification challenge.

Intelligent Marine Survey: Lightweight Multi-Scale Attention Adaptive Segmentation Framework for Underwater Target Detection of AUV

Intelligent Marine Survey: Lightweight Multi-Scale Attention Adaptive Segmentation Framework for Underwater Target Detection of AUV