About this Research Topic
Illegal, unreported, and unregulated (IUU) fishing damages marine ecosystems and poses a serious threat to food security. IUU fishing as a multi-billion profit-making transnational and organized crime imposes a whopping cost on the nations' economies. Recognizing and understanding the negative impact of IUU fishing activities by industrial fleets on the economy and environment is the first step toward combating it, and effective enforcement of fisheries law is a key requirement in this regard. The large number of fishing vessels active in the open ocean makes fisheries control and compliance challenging. This situation calls for innovative and pragmatic solutions and strategies to tackle the IUU fishing problem.
Big data solutions significantly contributed to solving many real-world problems in the last decade. Recent technological progress results in massive marine traffic data which provides detailed information about vessels activities. Learned patterns from vessels movement data can be used for effective fisheries monitoring and enforcement. Processing vast amounts of vessels movement data is critical yet challenging for detecting suspicious activities for the prevention, deterrence and intervention of illegal operations. Machine and deep learning leverage computational power to process and turn vast amounts of data into actionable knowledge.
The goal of this Research Topic is designing data-driven algorithms, systems and services using state-of-the-art computational models to improve maritime domain awareness and control IUU fishing.
We welcome original contributions centered on IUU fishing and its impact on food system sustainability. This Research Topic aims at bringing together current knowledge on illegal and unsustainable fishing by academia, government and industry with the goal of fostering and expanding computational multidisciplinary studies toward achieving more sustainable fisheries management. Submissions are invited on the following themes (but not limited to):
-Quantitative estimation of IUU fishing and its impact on resource sustainability
-Improved enforcement actions against IUU fishing to enhance food and nutrition security
-Economic driver, cost and consequence of illegal fishing
-Negative impact of regulations associated with IUU fishing on small-scale fisheries
-Strategies for focused-deterrence and selective targeting of vessels involved in IUU fishing
-AI/ML-based solutions to enhance maritime domain awareness
-Heterogeneous data mining from multiple vessels movement data source
Big data solutions significantly contributed to solving many real-world problems in the last decade. Recent technological progress results in massive marine traffic data which provides detailed information about vessels activities. Learned patterns from vessels movement data can be used for effective fisheries monitoring and enforcement. Processing vast amounts of vessels movement data is critical yet challenging for detecting suspicious activities for the prevention, deterrence and intervention of illegal operations. Machine and deep learning leverage computational power to process and turn vast amounts of data into actionable knowledge.
The goal of this Research Topic is designing data-driven algorithms, systems and services using state-of-the-art computational models to improve maritime domain awareness and control IUU fishing.
We welcome original contributions centered on IUU fishing and its impact on food system sustainability. This Research Topic aims at bringing together current knowledge on illegal and unsustainable fishing by academia, government and industry with the goal of fostering and expanding computational multidisciplinary studies toward achieving more sustainable fisheries management. Submissions are invited on the following themes (but not limited to):
-Quantitative estimation of IUU fishing and its impact on resource sustainability
-Improved enforcement actions against IUU fishing to enhance food and nutrition security
-Economic driver, cost and consequence of illegal fishing
-Negative impact of regulations associated with IUU fishing on small-scale fisheries
-Strategies for focused-deterrence and selective targeting of vessels involved in IUU fishing
-AI/ML-based solutions to enhance maritime domain awareness
-Heterogeneous data mining from multiple vessels movement data source
Keywords: Fisheries Resource Management, Maritime Domain Awareness, Spatiotemporal Data Mining, Machine and Deep Learning, IUU Fishing
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
