Date of Award:
8-2024
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Committee Chair(s)
Mario Harper
Committee
Mario Harper
Committee
Vladimir Kulyukin
Committee
John Edwards
Abstract
Illegal fishing activities pose a significant threat to the sustainability of marine ecosystems and the economies and societies which rely on them. Detection of fishing vessels engaging in illegal activity is difficult, as many ships engaging in such activity actively avoid detection through radio systems used for maritime traffic monitoring. Satellite imagery provides a promising means for detecting fishing vessels, though designing an effective system is difficult due to limited availability of labeled image datasets of fishing vessels. This research proposes a system to detect illegal fishing activity through the use of a low-power ship detection satellite and proposes a decision-making process capable of analyzing ship movements and location to determine if a ship is engaging in illegal fishing. To overcome current limitations in available image datasets with labeled fishing vessels, this research proposes a new method for expanding existing image datasets to improve ship detection performance. The proposed illegal fishing detection system is further designed to be capable of weighing various social, economic, and ecological factors involved when determining a response to an incident of illegal fishing.
Checksum
388109d483afabdcff6cebf2ee65cfcd
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Nelson, Kyler E., "Fishing Vessel Detection in Exclusive Economic Zones From Low Earth Orbit Satellites With Power and Computational Constraints" (2024). All Graduate Theses and Dissertations, Fall 2023 to Present. 265.
https://digitalcommons.usu.edu/etd2023/265
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