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Detecting Illegal Fishing

Project Description

By ingesting fishing vessel tracking data, I will train a neural network to classify vessels and detect a variety of fishing events. The network will be fed AIS (Automatic Identification System) data, which is a required tracking system that uses GPS sensors on ships, and potentially VMS (Vessel Monitoring System) data as well.

Fig 1. Data Files & Variables
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Fig 2. AIS data from a troller ship
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Fig 3. Mapped data points for long liner and reefer fishing activities
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Combining this identification method with other datasets from Global Fishing Watch, the vessel’s activities can be categorized as either legal or illegal, depending on parameters such as country of origin and local maritime laws.

Since overfishing and destructive fishing methods impart a tremendous burden on Earth’s oceanic ecosystem, the identification of fishing patterns is key to catching and halting illegal fishing methods as soon as possible.

Project Goals

  1. Use Global Fishing Watch’s dataset to train a model that can identify different types of fishing behavior.
  2. Apply the model to Global Fishing Watch’s testing dataset to categorize fishing behaviors.
  3. (Longer Term) Can we predict the fishing behaviors with less data? That is, in real time?