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Model fishing activity patterns based on weather information through machine learning algorithms to help devising optimal ocean patrolling routes.

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The-Fishing-Games

!!! UNFINISHED PROJECT !!!

Datasets

Code used to download and convert from netCDF4 to CSV the following hourly weather variables

  • time
  • latitude
  • longitude
  • 10m_u_component_of_wind
  • 10m_v_component_of_wind
  • maximum_individual_wave_height
  • mean_wave_period
  • peak_wave_period
  • period_corresponding_to_maximum_individual_wave_height
  • significant_height_of_combined_wind_waves_and_swell

from the ERA5 dataset between the years 2012 and 2019, as well as the whole anonymized AIS training data from the Global Fishing Watch dataset between the same period of time.

Both datasets are then cleaned and merged based on time, latitude and longitude to create a final augmented dataset on which to train machine learning models to predict fishing activity patterns based on weather information.

Dataset Schema

  • time
  • latitude
  • longitude
  • distance_from_shore
  • distance_from_port
  • 10m_u_component_of_wind
  • 10m_v_component_of_wind
  • mean_wave_period
  • peak_wave_period
  • maximum_individual_wave_height
  • period_corresponding_to_maximum_individual_wave_height
  • significant_height_of_combined_wind_waves_and_swell
  • is_fishing

Code

Simply run the following command

./generate_data.sh

to run the whole process.

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Model fishing activity patterns based on weather information through machine learning algorithms to help devising optimal ocean patrolling routes.

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