Using AIS to Attempt a Quantitative Evaluation of Unobserved Trawling Activity in the Mediterranean Sea

Ferrà, Carmen; Tassetti, Anna Nora; Armelloni, Enrico Nicola; Galdelli, Alessandro; Scarcella, Giuseppe; Fabi, Gianna

doi:10.3389/fmars.2020.580612

Cited by 20 publications

(14 citation statements)

References 32 publications

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“…In addition, individual countries may require AIS usage on additional vessels. For example, AIS is required for EU fishing vessels >15 m in length 31 . Moreover, AIS is also increasingly used on a voluntary basis by many other vessels, including smaller fishing and leisure craft, thereby providing a unique opportunity to monitor the location of a diversity of vessels across the world 28 – 30 .…”

Section: Introductionmentioning

confidence: 99%

“…Despite some limitations of the system (e.g. small vessels not equipped with AIS, and transmission gaps 31 ), historical and real-time AIS data have been shown to provide unparalleled insights into shipping-derived impacts and conservation planning at multiple spatial and temporal scales 32 – 35 . With regard to COVID-19, AIS has recently been employed to assess the potential spread of the virus 13 , 36 , 37 and to describe the reductions in marine traffic at local scales 11 .…”

Section: Introductionmentioning

confidence: 99%

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Tracking the global reduction of marine traffic during the COVID-19 pandemic

et al. 2021

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The COVID-19 pandemic has resulted in unparalleled global impacts on human mobility. In the ocean, ship-based activities are thought to have been impacted due to severe restrictions on human movements and changes in consumption. Here, we quantify and map global change in marine traffic during the first half of 2020. There were decreases in 70.2% of Exclusive Economic Zones but changes varied spatially and temporally in alignment with confinement measures. Global declines peaked in April, with a reduction in traffic occupancy of 1.4% and decreases found across 54.8% of the sampling units. Passenger vessels presented more marked and longer lasting decreases. A regional assessment in the Western Mediterranean Sea gave further insights regarding the pace of recovery and long-term changes. Our approach provides guidance for large-scale monitoring of the progress and potential effects of COVID-19 on vessel traffic that may subsequently influence the blue economy and ocean health.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking the global reduction of marine traffic during the COVID-19 pandemic

et al. 2021

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“…Recent studies highlighted the enormous potential that the cooperative AIS offers in providing detailed vessel movements and classifying fishing activities [ 15 , 16 , 17 ], while others investigated its reliability by applying statistical and machine-learning solutions to detect anomaly in maritime behavior [ 18 , 19 ]. AIS position reports can indeed drop out for many reasons, such as weak signals, signal interference in crowded areas or intentionally tampering when entering port or in close proximity of fishery managed areas [ 20 , 21 ]. Moreover, AIS is adopted by only a fraction of vessels (≥15 m in Length Over All).…”

Section: Introductionmentioning

confidence: 99%

A Synergic Integration of AIS Data and SAR Imagery to Monitor Fisheries and Detect Suspicious Activities

Galdelli

Mancini

Ferrà

et al. 2021

Sensors

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Maritime traffic and fishing activities have accelerated considerably over the last decade, with a consequent impact on the environment and marine resources. Meanwhile, a growing number of ship-reporting technologies and remote-sensing systems are generating an overwhelming amount of spatio-temporal and geographically distributed data related to large-scale vessels and their movements. Individual technologies have distinct limitations but, when combined, can provide a better view of what is happening at sea, lead to effectively monitor fishing activities, and help tackle the investigations of suspicious behaviors in close proximity of managed areas. The paper integrates non-cooperative Synthetic Aperture Radar (SAR) Sentinel-1 images and cooperative Automatic Identification System (AIS) data, by proposing two types of associations: (i) point-to-point and (ii) point-to-line. They allow the fusion of ship positions and highlight “suspicious” AIS data gaps in close proximity of managed areas that can be further investigated only once the vessel—and the gear it adopts—is known. This is addressed by a machine-learning approach based on the Fast Fourier Transform that classifies single sea trips. The approach is tested on a case study in the central Adriatic Sea, automatically reporting AIS-SAR associations and seeking ships that are not broadcasting their positions (intentionally or not). Results allow the discrimination of collaborative and non-collaborative ships, playing a key role in detecting potential suspect behaviors especially in close proximity of managed areas.

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“…Technological improvements may reverse such condition. For instance, the spread adoption of reporting technologies and remote sensing systems, such as vessel monitoring system (VMS) and automatic identification system (AIS), are generating an overwhelming amount of reliable, spatio-temporal and geographically distributed data related to large-size vessels and their movements, which could enhance the maritime knowledge if analyzed and modeled [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Ecosystem-Based MSP for Enhanced Fisheries Sustainability: An Example from the Northern Adriatic (Chioggia—Venice and Rovigo, Italy)

et al. 2021

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Human pressures on marine ecosystems significantly increased during last decades. Among the intense anthropic activities, industrial fisheries have caused the alteration of habitats, the reduction of biodiversity and the main fish stocks. The aim of this research, carried out in the Adriatic Sea, was to test a repeatable Marine Spatial Planning framework aimed at enhancing fisheries sustainability through the application of Decision Support Tools and the composition of a catalog of possible measures. The use of these tools proved very useful to identify possible criticalities and facilitate an effective exchange with fisheries stakeholders, local authorities, and fishermen, whose involvement was an indispensable step in the process. Tool-based analyses allowed to assess the spatial footprint of a range of anthropogenic pressures from human activities (e.g., fisheries, maritime traffic, and aquaculture). Within this multi-pressure scenario, special attention was paid to fishing-related disturbances and potential conflicts across different fishing métier and with other sectors. Specifically, results highlighted the spatial features of the major fishing pressures (e.g., abrasion from trawling) affecting essential fish habitats, marine mammals and turtles in the study area. A portfolio of possible management measures is identified for the study area. It provides clear evidence that, in order to mitigate emerging conflicts and cumulative impacts, it is necessary to combine and integrate different types of measures: spatial measures modulated over time, monitoring and control, actions to fill knowledge gaps, concertation—involvement—co-management actions, improvement of governance systems, actions to support innovation in the sector, etc. Given the complex set of measures discussed, this work can provide a useful contribution to the management of fisheries both at local and regional level, fostering the transition to sustainable fisheries.

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Using AIS to Attempt a Quantitative Evaluation of Unobserved Trawling Activity in the Mediterranean Sea

Cited by 20 publications

References 32 publications

Tracking the global reduction of marine traffic during the COVID-19 pandemic

Tracking the global reduction of marine traffic during the COVID-19 pandemic

A Synergic Integration of AIS Data and SAR Imagery to Monitor Fisheries and Detect Suspicious Activities

Ecosystem-Based MSP for Enhanced Fisheries Sustainability: An Example from the Northern Adriatic (Chioggia—Venice and Rovigo, Italy)

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