A Feature Encoding Approach and a Cloud Computing Architecture to Map Fishing Activities

2021 ◽  
Author(s):  
A. Galdelli ◽  
A. Mancini ◽  
E. Frontoni ◽  
A. N. Tassetti
Keyword(s):  
Spatial Planning ◽  
Low Cost ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Marine Spatial Planning ◽  
Fishing Activity ◽  
Feature Encoding ◽  
Encoding Method ◽  
New Policies

Abstract Monitoring fish stocks and fleets’ activities is key for Marine Spatial Planning. In recent years Vessel Monitoring System and Automatic Identification System have been developed for vessels longer than 12 and 15m in length, respectively, while small scale vessels (< 12m in length) remain untracked and largely unregulated, even though they account for 83% of all fishing activity in the Mediterranean Sea. In this paper we present an architecture that makes use of a low-cost LoRa/cellular network to acquire and process positioning data from small scale vessels, and a feature encoding approach that can be easily extended to process and map small scale fisheries. The feature encoding method uses a Markov chain to model transitions between successive behavioural states (e.g., fishing, steaming) of each vessel and classify its activity. The approach is evaluated using k-fold and Leave One Boat Out cross-validations and, in both cases, it results in significant improvements in the classification of fishing activities. The use of a such low-cost and open source technology coupled to artificial intelligence could open up potential for more integrated and transparent platforms to inform coastal resource and fisheries management, and cross-border marine spatial planning. It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to the optimal use of marine resources.

scholarly journals AIS and VMS Ensemble Can Address Data Gaps on Fisheries for Marine Spatial Planning

2021 ◽  
Vol 13 (7) ◽  
pp. 3769
Author(s):  
Pascal Thoya ◽  
Joseph Maina ◽  
Christian Möllmann ◽  
Kerstin S. Schiele
Keyword(s):  
Case Studies ◽  
Spatial Planning ◽  
Fishing Effort ◽  
Rapid Expansion ◽  
Automatic Identification ◽  
Identification System ◽  
Marine Spatial Planning ◽  
The North ◽  
Address Data ◽  
The Baltic

Spatially explicit records of fishing activities’ distribution are fundamental for effective marine spatial planning (MSP) because they can help to identify principal fishing areas. However, in numerous case studies, MSP has ignored fishing activities due to data scarcity. The vessel monitoring system (VMS) and the automatic identification system (AIS) are two commonly known technologies used to observe fishing activities. However, both technologies generate data that have several limitations, making them ineffective when used in isolation. Here, we evaluate both datasets’ limitations and strengths, measure the drawbacks of using any single dataset and propose a method for combining both technologies for a more precise estimation of the distribution of fishing activities. Using the Baltic Sea and the North Sea–Celtic Sea regions as case studies, we compare the spatial distribution of fishing effort from International Council for the Exploration of the Seas (ICES) VMS data and global fishing watch AIS data. We show that using either dataset in isolation can lead to a significant underestimation of fishing effort. We also demonstrate that integrating both datasets in an ensemble approach can provide more accurate fisheries information for MSP. Given the rapid expansion of MSP activities globally, our approach can be utilised in data-limited regions to improve cross border spatial planning.

A Cloud Computing Architecture to Map Trawling Activities Using Positioning Data

2019 ◽  
Author(s):  
A. Galdelli ◽  
A. Mancini ◽  
A. N. Tassetti ◽  
C. Ferrà Vega ◽  
E. Armelloni ◽  
...  
Keyword(s):  
Integrated Management ◽  
Low Cost ◽  
Sustainable Use ◽  
Fishing Effort ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Small Vessels ◽  
Small Scale Fisheries ◽  
Major Development

Abstract Descriptive and spatially-explicit information on fisheries plays a key role for an efficient integrated management of the maritime activities and the sustainable use of marine resources. However, this information is today still hard to obtain and, consequently, is a major issue for implementing Marine Spatial Planning (MSP). Since 2002, the Automatic Identification System (AIS) has been undergoing a major development allowing now for a real time geo-tracking and identification of equipped vessels of more than 15m in length overall (LOA) and, if properly processed, for the production of adequate information for MSP. Such monitoring systems or other low-cost and low-burden solutions are still missing for small vessels (LOA < 12m), whose catches and fishing effort remain spatially unassessed and, hence, unregulated. In this context, we propose an architecture to process vessel tracking data, understand the behaviour of trawling fleets and map related fishing activities. It could be used to process not only AIS data but also positioning data from other low cost systems as IoT sensors that share their position over LoRa and 2G/3G/4G links. Analysis gives back important and verified data (overall accuracy of 92% for trawlers) and opens up development perspectives for monitoring small scale fisheries, helping hence to fill fishery data gaps and obtain a clearer picture of the fishing grounds as a whole.

scholarly journals A comparison of VMS and AIS data: the effect of data coverage and vessel position recording frequency on estimates of fishing footprints

2017 ◽  
Vol 75 (3) ◽  
pp. 988-998 ◽  
Author(s):  
Jennifer L Shepperson ◽  
Niels T Hintzen ◽  
Claire L Szostek ◽  
Ewen Bell ◽  
Lee G Murray ◽  
...  
Keyword(s):  
Missing Data ◽  
Monitoring System ◽  
Spline Interpolation ◽  
Automatic Identification ◽  
Identification System ◽  
Fishing Activity ◽  
Fishing Vessels ◽  
Position Data ◽  
Hermite Spline ◽  
Data Coverage

Abstract Understanding the distribution of fishing activity is fundamental to quantifying its impact on the seabed. Vessel monitoring system (VMS) data provides a means to understand the footprint (extent and intensity) of fishing activity. Automatic Identification System (AIS) data could offer a higher resolution alternative to VMS data, but differences in coverage and interpretation need to be better understood. VMS and AIS data were compared for individual scallop fishing vessels. There were substantial gaps in the AIS data coverage; AIS data only captured 26% of the time spent fishing compared to VMS data. The amount of missing data varied substantially between vessels (45–99% of each individuals' AIS data were missing). A cubic Hermite spline interpolation of VMS data provided the greatest similarity between VMS and AIS data. But the scale at which the data were analysed (size of the grid cells) had the greatest influence on estimates of fishing footprints. The present gaps in coverage of AIS may make it inappropriate for absolute estimates of fishing activity. VMS already provides a means of collecting more complete fishing position data, shielded from public view. Hence, there is an incentive to increase the VMS poll frequency to calculate more accurate fishing footprints.

scholarly journals Lockdown: How the COVID-19 Pandemic Affected the Fishing Activities in the Adriatic Sea (Central Mediterranean Sea)

2021 ◽  
Vol 8 ◽  
Author(s):  
Elisabetta Russo ◽  
Marco Anelli Monti ◽  
Giacomo Toninato ◽  
Claudio Silvestri ◽  
Alessandra Raffaetà ◽  
...  
Keyword(s):  
Venice Lagoon ◽  
Fishing Effort ◽  
Otter Trawl ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Strong Reduction ◽  
Central Mediterranean ◽  
Containment Measures ◽  
Almost All

The coronavirus disease 2019 (COVID-19) has brought a global socio-economic crisis to almost all sectors including the fishery. To limit the infection, governments adopted several containment measures. In Italy, Croatia, and Slovenia, a lockdown period was imposed from March to May 2020, during which many activities, including restaurants had to close or limit their business. All of this caused a strong reduction in seafood requests and consequently, a decrease in fishing activities. The aim of this study is to investigate the effects of the COVID-19 in the Northern and Central Adriatic fleet, by comparing the fishing activities in three periods (before, during, and after the lockdown) of 2019 and 2020. The use of the Automatic Identification System (AIS) data allowed us to highlight the redistribution of the fishing grounds of the trawlers, mainly located near the coasts during the 2020 lockdown period, as well as a reduction of about 50% of fishing effort. This reduction resulted higher for the Chioggia trawlers (−80%) and, in terms of fishing effort decrease, the large bottom otter trawl was the fishing segment mainly affected by the COVID-19 event. Moreover, by analysing the landings of the Chioggia fleet and the Venice lagoon fleets, it was possible to point out a strong reduction both in landings and profits ranging from −30%, for the small-scale fishery operating at sea, to −85%, for the small bottom otter trawl.

scholarly journals Global Fisheries Responses to Culture, Policy and COVID-19 from 2017 to 2020

2021 ◽  
Vol 13 (22) ◽  
pp. 4507
Author(s):  
Bin He ◽  
Fengqin Yan ◽  
Hao Yu ◽  
Fenzhen Su ◽  
Vincent Lyne ◽  
...  
Keyword(s):  
Large Data ◽  
Fishing Effort ◽  
Coastal Areas ◽  
Decision Makers ◽  
Small Scale ◽  
Automatic Identification ◽  
Identification System ◽  
Political Events ◽  
Open Source Data ◽  
The Us

Global Fishing Watch (GFW) provides global open-source data collected via automated monitoring of vessels to help with sustainable management of fisheries. Limited previous global fishing effort analyses, based on Automatic Identification System (AIS) data (2017–2020), suggest economic and environmental factors have less influence on fisheries than cultural and political events, such as holidays and closures, respectively. As such, restrictions from COVID-19 during 2020 provided an unprecedented opportunity to explore added impacts from COVID-19 restrictions on fishing effort. We analyzed global fishing effort and fishing gear changes (2017–2019) for policy and cultural impacts, and then compared impacts of COVID-19 lockdowns across several countries (i.e., China, Spain, the US, and Japan) in 2020. Our findings showed global fishing effort increased from 2017 to 2019 but decreased by 5.2% in 2020. We found policy had a greater impact on monthly global fishing effort than culture, with Chinese longlines decreasing annually. During the lockdown in 2020, trawling activities dropped sharply, particularly in the coastal areas of China and Spain. Although Japan did not implement an official lockdown, its fishing effort in the coastal areas also decreased sharply. In contrast, fishing in the Gulf of Mexico, not subject to lockdown, reduced its scope of fishing activities, but fishing effort was higher. Our study demonstrates, by including the dimensions of policy and culture in fisheries, that large data may materially assist decision-makers to understand factors influencing fisheries’ efforts, and encourage further marine interdisciplinary research. We recommend the lack of data for small-scale Southeast Asian fisheries be addressed to enable future studies of fishing drivers and impacts in this region.

Hidden Markov Model(HMM)-Based Fishing Activity Prediction Using V-Pass Data

2021 ◽  
Vol 8 (4) ◽  
pp. 221-227
Author(s):  
Ju-Han Park ◽  
Ho-Kun Jeon ◽  
Chan-Su Yang
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Time Series Data ◽  
Hidden Markov ◽  
Series Data ◽  
Automatic Identification ◽  
Identification System ◽  
Research Station ◽  
Fishing Vessel ◽  
Fishing Activity

Illegal fishing has been a serious threat to the conservation of seafood resources and provoked the importance of marine surveillance. There are several types of fishing vessel monitoring systems operated by Republic of Korea, for example, Vessel Monitoring System(VMS), Automatic Identification System (AIS), V-Pass and VHF-DSC. However, those methods are not adaptable directly to fishing activity monitoring. The limitation requires more human resources to determine fishing status. Thus, this study proposes a method of estimating fishing activity from V-Pass, fishing vessel position reporting system, using Hidden Markov Model (HMM). HMM is a model to determine status through probability distribution for a sequence of time-series data. First of all, fishing activity status was labeled on V-Pass data. The distribution of speed on fishing activity was computed from the labeled data and HMM was constructed from the data obtained at Socheongcho Ocean Research Station (SORS). The model was first applied to the data of SORS for a test, and then Busan for validation. The model showed 99.4% and 89.6% as test and validation accuracy, respectively. It is concluded that the HMM can be applicable to predict a fishing activity from vessel tracks.

Fishing for administrative justice in marine spatial planning: Small-scale fishers’ right to written reasons

2021 ◽  
Vol 2021 ◽  
pp. 122-146
Author(s):  
Rachael Chasakara ◽  
Ntemesha Maseka
Keyword(s):  
South Africa ◽  
Working Group ◽  
Spatial Planning ◽  
Small Scale ◽  
Marine Spatial Planning ◽  
Administrative Action ◽  
Space And Time ◽  
Constitutional Right ◽  
Administrative Justice ◽  
Ocean Zoning

The emergence of marine spatial planning (MSP) has been ascribed to the inability of the ocean spaces to meet all demands simultaneously. With increasing uses and users of the ocean comes a rise in conflicts. Studies that sought to reduce those conflicts have shown the benefits of zoning the ocean in space and time. In South Africa, the Department of Environment, Forestry and Fisheries, which functions through a national working group (NWG) on MSP, is responsible for the implementation of MSP, which includes ocean zoning in South Africa’s ocean spaces. In the implementation of MSP, the NWG will make decisions which, this article argues, constitute administrative action triggering the constitutional right to written reasons. This article examines the small-scale fishers’ right to written reasons following a decision by the NWG. It concludes that the NWG does have an obligation to fulfil this right and that the MSP instruments are drafted in a manner that supports this duty.

scholarly journals Operational Monitoring of Illegal Fishing in Ghana through Exploitation of Satellite Earth Observation and AIS Data

2019 ◽  
Vol 11 (3) ◽  
pp. 293 ◽  
Author(s):  
Andrey Kurekin ◽  
Benjamin Loveday ◽  
Oliver Clements ◽  
Graham Quartly ◽  
Peter Miller ◽  
...  
Keyword(s):  
Earth Observation ◽  
Integrated System ◽  
Economic Damage ◽  
Automatic Identification ◽  
Identification System ◽  
Observation Data ◽  
Constant False Alarm Rate ◽  
Fishing Activity ◽  
Iuu Fishing ◽  
Geographical Regions

Over the last decade, West African coastal countries, including Ghana, have experienced extensive economic damage due to illegal, unreported and unregulated (IUU) fishing activity, estimated at about USD 100 million in losses each year. Illegal, unreported and unregulated fishing poses an enormous threat to the conservation and management of the dwindling fish stocks, causing multiple adverse consequences for fisheries, coastal and marine ecosystems and for the people who depend on these resources. The Integrated System for Surveillance of Illegal, Unlicensed and Unreported Fishing (INSURE) is an efficient and inexpensive system that has been developed for the monitoring of IUU fishing in Ghanaian waters. It makes use of fast-delivery Earth observation data from the synthetic aperture radar instrument on Sentinel-1 and the Multi Spectral Imager on Sentinel-2, detecting objects that differ markedly from their immediate background using a constant false alarm rate test. Detections are matched to, and verified by, Automatic Identification System (AIS) data, which provide the location and dimensions of ships that are legally operating in the region. Matched and unmatched data are then displayed on a web portal for use by coastal management authorities in Ghana. The system has a detection success rate of 91% for AIS-registered vessels, and a fast throughput, processing and delivering information within 2 h of acquiring the satellite overpass. However, over the 17-month analysis period, 75% of SAR detections have no equivalent in the AIS record, suggesting significant unregulated marine activity, including vessels potentially involved in IUU. The INSURE system demonstrated its efficiency in Ghana’s exclusive economic zone and it can be extended to the neighbouring states in the Gulf of Guinea, or other geographical regions that need to improve fisheries surveillance.

scholarly journals Effect of temporal and spatial resolution on identification of fishing activities in small-scale fisheries using pots and traps

2019 ◽  
Vol 76 (6) ◽  
pp. 1601-1609 ◽  
Author(s):  
Tania Mendo ◽  
Sophie Smout ◽  
Tommaso Russo ◽  
Lorenzo D’Andrea ◽  
Mark James
Keyword(s):  
Spatial Distribution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Low Cost ◽  
Grid Cell ◽  
Analysis Data ◽  
Satellite System ◽  
Small Scale ◽  
Fishing Activity ◽  
Small Scale Fisheries

Abstract Analysis of data from vessel monitoring systems and automated identification systems in large-scale fisheries is used to describe the spatial distribution of effort, impact on habitats, and location of fishing grounds. To identify when and where fishing activities occur, analysis needs to take account of different fishing practices in different fleets. Small-scale fisheries (SSFs) vessels have generally been exempted from positional reporting requirements, but recent developments of compact low-cost systems offer the potential to monitor them effectively. To characterize the spatial distribution of fishing activities in SSFs, positions should be collected with sufficient frequency to allow detection of different fishing behaviours, while minimizing demands for data transmission, storage, and analysis. This study sought to suggest optimal rates of data collection to characterize fishing activities at appropriate spatial resolution. In a SSF case study, on-board observers collected Global Navigation Satellite System (GNSS) position and fishing activity every second during each trip. In analysis, data were re-sampled to lower temporal resolutions to evaluate the effect on the identification of number of hauls and area fished. The effect of estimation at different spatial resolutions was also explored. Consistent results were found for polling intervals <60 s in small vessels and <120 in medium and large vessels. Grid cell size of 100 × 100 m resulted in best estimations of area fished. Remote collection and analysis of GNSS or equivalent data at low cost and sufficient resolution to infer small-scale fisheries activities. This has significant implications globally for sustainable management of these fisheries, many of which are currently unregulated.

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