Search Results (45)

The frequent occurrence of collision accidents between merchant and fishing vessels in China’s offshore waters not only threatens human lives and property, but also disrupts shipping and fishing activities and may cause marine environmental pollution. To effectively reduce such accidents and increase maritime safety in Chinese coastal waters, this study integrates association rules with complex networks to develop a directed weighted network of causal factors. Grounded theory and the Human Factors Analysis and Classification System (HFACS) are applied to identify and categorize causal factors from 152 collision accident investigation reports. Potential causal relationships are mined using the association rule, which is then applied to construct the causal network. Finally, the topological characteristics of the network are analyzed. The results reveal that serious negligence in lookout, failure to assess collision risks properly, and failure to adopt a safe speed significantly impact collision accidents. These findings highlight the necessity of implementing targeted preventive measures to address critical factors. This study provides valuable insights for maritime stakeholders to develop effective strategies. Full article

The common dolphin, Delphinus delphis, is the most abundant cetacean species along the western Iberian Peninsula and faces many anthropogenic threats, with bycatch being the most impactful. Its preferred prey, sardine (Sardina pilchardus), has shown fluctuating abundance over the past decade, potentially influencing dolphin distribution. This study provides the first insights into common dolphin distribution along the western Iberian coast, using sighting data from vessel research surveys (2005–2020) to identify hotspot areas while accounting for monthly and seasonal distributions overlapping with sardine abundance. Common dolphin hotspots were located along the central–western and southern Portuguese mainland coasts, coinciding with important fishing ports, oceanographic features, and sardine juvenile habitats. Furthermore, during 2013–2016, common dolphins were observed significantly farther from the coast, coinciding with a period of particularly low coastal sardine biomass. However, GAM analysis indicated that the relationship between sardine biomass and the distance of common dolphins was not significant. This study highlights the major common dolphin hotspots and presents the most comprehensive temporal and distribution maps of the common dolphin along the western Iberian coast, particularly in response to sardine availability. These results can be used by managers to inform conservation measures and for the sustainable management of the Portuguese sardine purse seine fishery fleet, which interacts the most with the species. Full article

Boating tourism in coastal–maritime areas often overlaps spatially and temporally with other economic activities, such as fishing, leading to complex interactions. These interactions can create opportunities for positive cooperation or generate conflicts that pressure natural resources and stakeholders. The aim of this study is to show whether or not there is evidence of interactions between fishing (n_f = 43) and tourism/recreation (n_t = 65) vessels. This study focuses on the interaction between maritime tourism activities and fishing in southern Portugal, using a social network analysis (SNA) approach based on automatic identification system (AIS) data to evaluate spatial and temporal patterns. The findings reveal that tourism activities dominate zones closer to the coast, with intermediate areas serving as shared spaces where interactions between vessel activities are more likely to occur. There was evidence of occasional interactions between a few recreational and fishing vessels (two passengers and three seiners), but the inferences from the results are insufficient to demonstrate how beneficial they are for both activities. Full article

This study investigated the status of anchors for small fishing vessels that correspond with the risk factors of submarine cables, which are essential elements for offshore wind farms. As for target vessels, small coastal fishing vessels of less than ten tons were divided into four categories by tonnage, and 71 locations were compared from a total of 59 fishing vessels. In the results, the shank showed a difference of approximately 18.2% from 119.3 to 145.8 cm on average, while the stock exhibited a difference of approximately 18.9% from 130.3 to 160.6 cm. The size of the anchor, however, was not proportional to the increase in the tonnage of the fishing vessel, and the anchors were produced in their own forms, based on the experience of the crew in many cases. In the statistical processing results, significant differences occurred in all areas except for the fluke. The stock and shank, which affect the dragging anchor, showed significant differences at a level of p < 0.05 while the bill, bill to bill, and bill to shank exhibited differences at a level of p < 0.01. This indicates that standardized criteria are required for the anchors of small coastal fishing vessels of less than ten tons, and that design standards for materials and reinforcements also need to be prepared as thin rebars or wooden columns are used, in addition to steel pipes, as the materials of the stock in many cases. Full article

Illegal, unreported, and unregulated (IUU) fishing significantly threatens marine ecosystems, disrupts the ecological balance of the oceans, and poses serious challenges to global fisheries management. This contribution presents the efficacy of China’s summer fishing moratorium using BeiDou vessel monitoring system (VMS) data from 2805 fishing vessels in the East China Sea and Yellow Sea, integrated with a deep learning framework for spatiotemporal analysis. A preprocessing protocol addressing multidimensional noise in raw VMS datasets was developed, incorporating velocity normalization and gap filling to ensure data reliability. The CNN-BiLSTM hybrid model emerged as optimal for fishing behavior classification, achieving 89.98% accuracy and an 87.72% F1 score through synergistic spatiotemporal feature extraction. Spatial analysis revealed significant policy-driven reductions in fishing intensity during the moratorium (May–August), with hotspot areas suppressed to sporadic coastal distributions. However, concentrated vessel activity in Zhejiang’s nearshore waters suggested potential illegal fishing. Post-moratorium, fishing hotspots expanded explosively, peaking in October and clustering in Yushan, Zhoushan, and Yangtze River estuary fishing grounds. Quarterly patterns identified autumn–winter 2021 as peak fishing seasons, with hotspots covering >80% of East China Sea grounds. The framework enables real-time fishing state detection and adaptive spatial management via dynamic closure policies. The findings underscore the need for strengthened surveillance during moratoriums and post-ban catch regulation to mitigate overfishing risks. Full article

Maritime communication networks are critical for supporting the increasing demands of oceanic and coastal activities, including shipping, fishing, and offshore operations. However, traditional systems face significant challenges in providing reliable, high-throughput connectivity due to dynamic sea environments, mobility, and non-line-of-sight (NLoS) conditions. Reconfigurable intelligent surfaces (RISs) have been proposed as a promising solution to overcome these limitations by enabling programmable control of electromagnetic wave propagation in next-generation mobile communication networks, such as beyond fifth generation and sixth generation ones (B5G/6G). This paper presents a deep learning-based (DL) scheme for beam selection in RIS-aided maritime next-generation networks. The proposed approach leverages deep learning to optimize beam selection dynamically, enhancing signal quality, coverage, and network efficiency in complex maritime environments. By integrating RIS configurations with data-driven insights, the proposed framework adapts to changing channel conditions and potential vessel mobility while minimizing latency and computational overhead. Simulation results demonstrate significant improvements in both machine learning (ML) metrics, such as beam selection accuracy, and overall communication reliability compared to traditional methods. More specifically, the proposed scheme reaches around 99% Top-$K$ Accuracy levels while jointly improving energy efficiency (ee) and spectral efficiency (SE) by approx. 2 times compared to state-of-the-art approaches. This study provides a robust foundation for employing DL in RIS-aided maritime networks, contributing to the advancement of intelligent, high-performance wireless communication systems for advanced maritime applications, such as autonomous mooring, the autonomous approach, and just-in-time arrival (JIT). Full article

Fisheries and aquaculture play a crucial role in global food security, yet species mislabeling remains a persistent challenge, undermining consumer trust and market transparency. Proper food labeling is essential for protecting public health due to the presence of unknown toxic or allergenic substances and preventing illegally sourced products from entering the market. Despite extensive research across Europe, seafood mislabeling in Croatia has remained unexplored. This study aims to provide the first comprehensive assessment of seafood labeling accuracy in Croatia, where fisheries are integral to the coastal economies and tourism. Using DNA barcoding of the COI gene, 109 seafood samples were collected over two years from various sources, including restaurants, markets, and fishing vessels, and analyzed for potential mislabeling. Results revealed a mislabeling rate of 3% among fish samples and 20% among cephalopods, with notable substitutions, such as the yellowfin tuna mislabeled as bigeye tuna and Bluefin tuna and the European squid mislabeled as Patagonian squid. Additionally, 38.5% of samples were partially labeled, while 32% lacked clear country-of-origin information, complicating traceability. While the findings align with the mislabeling rates in other European countries, this study underscores the ongoing challenges in seafood labeling compliance. Establishing standardized monitoring protocols will be essential for improving comparability and effectively addressing seafood fraud. Full article

Preventing collision accidents between merchant ships and fishing vessels has long been a significant challenge for maritime safety in coastal waters. To quantitatively analyze the relationship between the risk factors contributing to these collisions, identify the key factors leading to such accidents, and develop effective prevention strategies, the N-K model was employed to examine the risk coupling mechanisms involved. The model was based on an analysis of 132 collision incidents between merchant ships and fishing vessels in China’s coastal waters from 2013 to 2023. The characteristics of these collision accidents were investigated, and the risk factors were categorized into four distinct types: human, management, environmental, and ship factors. The coupling of collision risk factors between merchant ships and fishing vessels was mainly considered from the perspective of the overall system, and the N-K model was used to calculate the probability and risk values associated with the coupling of these four risk factors. Modeling results indicated that the coupling value of four factors was 0.1083, which was 1.5 times greater than the maximum coupling value of three factors and 2.1 times greater than the maximum coupling value of two factors. The risk of collision accidents between merchant ships and fishing vessels increases gradually with an increase in the risk coupling factors. Among the four categories of factors, the risk coupling between the ship factors and environmental factors is associated with a relatively large probability of accidents. Appropriate countermeasures were proposed to implement effective preventive measures at the source of collision accidents. Full article

Research on the extraction of satellite information for the areas of coastal fish cages and rafts is important to quickly grasp the pattern and structure of the coastal fishery aquaculture industry. This study proposes a multi-feature and rule-based object-oriented image classification (MROIC) model, integrating spatial-spectral enhancement techniques with object-based image analysis classification methods. The MROIC model enhances spectral information by constructing ratio bands alongside principal component analysis, subsequently employing rule sets, edge detection algorithms, and comprehensive algorithmic merging techniques. It is applicable to satellite image classification tasks in complex environments, including influence of clouds and vessels. The information of fish cage and raft facilities is extracted via the MROIC model on the southwest coast of Xiapu County, Fujian Province, as an example. The results showed that the MROIC model attained an average total classification accuracy of 90.43% and a Kappa coefficient of 0.80. Extracting the area of fisheries facilities under the influence of clouds and vessels can provide better extraction accuracy and lower omission error. The MROIC model proposed in this study demonstrates high extraction accuracy and strong applicability, offering technical support for government planning in fishery facility areas and aiding in the risk assessment and management efficiency of fishery facility insurance. Full article

This paper investigates the illegal activities that may negatively impact the environment in Croatia’s protected areas, particularly those associated with tourism. Failure Mode and Effects Analysis (FMEA) and sensitivity analysis are used to identify distinct high-risk activities specific to different park types. Coastal parks are found to be particularly vulnerable to maritime-related illegal activities, with high risk exposure from mooring vessels and swimming in prohibited areas. These parks also face significant risks from illegal fishing and the capture of strictly protected plants and animals, highlighting the need for enhanced marine ecosystem protection. Mountainous and forest parks face significant risks from fire-related activities, while wetland parks are sensitive to poaching and illegal fishing. Additionally, diverse landscape parks show increased vulnerability to littering, poaching, and the collection or harvesting of strictly protected plants and animals. The results underscore the necessity for tailored risk-management strategies that prioritize interventions based on park-specific challenges. By addressing the unique vulnerabilities of each park type, this study contributes insights into mitigating environmental threats posed by tourism and emphasizes the importance of continuous monitoring and adaptive management in protected areas. Full article

This study evaluates the economic benefits of meteorological information services (MISs) provided by the Central Weather Administration (CWA) in Taiwan, specifically for Taiwan’s capture fishery industry. Using the contingent valuation method (CVM) and conducting in-person interviews, we collected questionnaires from capture fishery practitioners nationwide to gather their subjective evaluations of the meteorological information services provided by the CWA. Based on these evaluations, we further investigated the respondents’ willingness to pay (WTP) for the CWA’s meteorological information services. An empirical analysis of the bid function was conducted to identify the key factors influencing the respondents’ bidding behavior. The empirical findings indicate that the primary factors affecting bids include subjective perceptions (such as forecast accuracy ratings and the ratings of the impacts on fishing production), working location, fishing vessel tonnage, and fishing methods. The median WTP for Taiwanese capture fishery practitioners is Taiwan dollar (TWD) 2111.12 per person per year. Based on the number of capture fishery practitioners in Taiwan in 2019, the total annual economic value of applying MIS in coastal and offshore fisheries is estimated to be between TWD 376 million and TWD 496 million per year. Full article

In multi-vessel collision avoidance decision-making, the collision between merchant and fishing vessels is a significant challenge. This paper proposes a fuzzy fusion method for making avoidance decisions under the influence of the navigation environment. First, C-means clustering was used to collect and analyze Automatic Identification System (AIS) data from fishing vessels. On this basis, the environment collision risk was determined using fuzzy reasoning. Second, the basic collision risk is obtained by calculating the DCPA and TCPA, and the integrated Collision Risk Index (CRI) is concluded by fuzzy logic through basic collision risk and the environment collision risk. The similar cases are extracted from the fuzzy case database, and collision avoidance decisions for merchant vessels are formulated following fuzzy adjustments. Finally, to validate the method, data from Chengshantou coastal waters is employed for verification. The results show that it can provide theoretical guidance and practical value for merchant vessels in making collision avoidance decisions. Full article

As coastal waters face constraints such as the deterioration of the aquaculture environment and limitations on the scale of operation, aquaculture will move towards the deep and distant sea. Large-scale aquaculture vessels are a new method of deep-sea aquaculture, and improving the utilisation efficiency of aquaculture tanks to ensure the best growth conditions for fish inside while ensuring the efficient discharge of particulate matter in these tanks will affect the productivity of aquaculture and the profitability of aquaculture vessels. This study investigated the effects of the tank structure ratio on the flow field characteristics and particulate removal efficiency in the aquaculture tanks of an aquaculture vessel. Numerical simulations of the flow field characteristics in the aquaculture tanks of an 8000 t-class aquaculture vessel at anchor were conducted using the FLOW-3D software to quantitatively evaluate the effects of the corner ratio on the fishability of aquaculture tanks and the efficiency of particulate emission using the parameters related to flow velocity, turbulence intensity, capacity utilisation rate, and particulate removal efficiency. The simulation results show that the tanks with corner structures have better flow field characteristics, which include a higher flow velocity, turbulence intensity, and discharge effect. When the corner length is more than 1/3 of the tank length, increasing the corner distance does not significantly enhance the optimisation of the flow field characteristics in the tank. Overall, this study’s results provide a reference basis for the structural design and optimisation of aquaculture tanks in aquaculture vessels. Full article

The invasion of ship domains stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying the collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validates it through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of the collision risk. Finally, taking the high-risk area for merchant and fishing vessel collisions in the Minjiang River Estuary as an example, this paper conducts an analysis that involves classifying ship collision scenarios, extracts risk data under different collision scenarios, and visually analyzes areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis are verified by the number of accidents that occurred in the most recent three years. Full article

A significant proportion of maritime incidents occurring in coastal waters are attributed to small fishing vessels. To analyze the root causes of such maritime accidents, it is imperative to conduct simulations to assess the potential pure loss of stability. This paper proposes a method of using a self-developed program to assess the vulnerability, which could be used in practice for seafarers to maintain shipping safety. To assess the vulnerability of three fishing vessels, the proposed method considers different wave conditions, where the parametric behaviors of the waves relative to the ship’s position (${\xi }_G/\lambda$) and wave steepness ($H/\lambda$) are explored. Additionally, vulnerability is computed systematically under diverse loading conditions, resulting in visual representations such as 2D and 3D plots. We conduct comparative simulations between the proposed method and the ICS-Hydro STAB. The simulation results reveal that the proposed method has superior accuracy in executing failure probability calculations. The prediction error is consistently below 5%. Full article