David Kroodsma

David Kroodsma leads Global Fishing Watch’s Research Program, which is a collaboration between Global Fishing Watch and a network of over 10 research institutions. He is responsible for leading and facilitating new research projects, and he works with the GFW engineering team to develop new technologies. David has over a decade and a half of experience working with NGOs and researchers to address global environmental challenges. He has a B.S. in physics and an M.S. in earth systems science from Stanford University.

Fishing localization using the vessel-scoring library

We published a logistic regression model for fishing localization a while a go as a python library built on top of scikit-learn. In this blog-post I’ll give you a quick introduction to how it can be used. The data we’re going to use is an AIS track exported from Google’s BigQuery, containing the columns timestamp (seconds since epoch), course (degrees) and speed (knots).

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