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A spatio-temporal matrix representation for trajectory classification

Published: 22 November 2024 Publication History

Abstract

Fish piracy remains widespread globally despite national and international efforts. Experts estimate it accounts for about 20% of the total seafood catch worldwide. Technology is playing a key role in detecting illegal fishing, with satellite imagery and sensors being used to track vessels and monitor fishing practices. Since fishing boats broadcast their positions using a vessel tracking system, this data can be processed to detect illegal activity. This study focuses on classifying fishing vessel trajectories using only positional data. A novel trajectory representation and a Convolutional Neural Network is employed, showing promising results compared to traditional methods.

References

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Buncha Chuaysi and Supaporn Kiattisin. 2020. Fishing Vessels Behavior Identification for Combating IUU Fishing: Enable Traceability at Sea. In Wireless Personal Communications. Springer.
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Hongda Duan, Fei Ma, Lixin Miao, and Canrong Zhang. 2022. A semi-supervised deep learning approach for vessel trajectory classification based on AIS data. Ocean & Coastal Management 218 (2022), 106015.
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Martha Dais Ferreira, Gabriel Spadon, Amilcar Soares, and Stan Matwin. 2022. A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels. Sensors 22, 16 (2022).
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Ioannis Kontopoulos, Konstantinos Chatzikokolakis, Konstantinos Tserpes, and Dimitris Zissis. 2020. Classification of vessel activity in streaming data. In 14th ACM International Conference on Distributed and Event-based Systems, DEBS 2020, Montreal, Quebec, Canada, July 13-17, 2020, Julien Gascon-Samson, Kaiwen Zhang, Khuzaima Daudjee, and Bettina Kemme (Eds.). ACM, 153--164.
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Amir Yaghoubi Shahir, Mohammad A. Tayebi, Uwe Glässer, Tilemachos Charalampous, Zahra Zohrevand, and Hans Wehn. 2019. Mining Vessel Trajectories for Illegal Fishing Detection. In 2019 IEEE International Conference on Big Data (IEEE BigData), Los Angeles, CA, USA, December 9-12, 2019, Chaitanya K. Baru, Jun Huan, Latifur Khan, Xiaohua Hu, Ronay Ak, Yuanyuan Tian, Roger S. Barga, Carlo Zaniolo, Kisung Lee, and Yanfang Fanny Ye (Eds.). IEEE, 1917--1927.
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cover image ACM Conferences
SIGSPATIAL '24: Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems
October 2024
743 pages
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 22 November 2024

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Author Tags

  1. AIS
  2. IUU fishing
  3. deep learning
  4. illegal fishing
  5. trajectory classification
  6. unregulated fishing
  7. unreported fishing

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SIGSPATIAL '24 Paper Acceptance Rate 37 of 122 submissions, 30%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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