Satellite Imagery and AI: A New Era in Ocean Conservation, from Research to Deployment and Impact

Patrick Beukema, Favyen Bastani, Piper Wolters, Henry Herzog, Joseph George Ferdinando

Keywords: Conservation, computer vision, machine learning, illegal fishing, IUU, NASA, ESA, sentinel-1, sentinel-2, VIIRS

TL;DR: Three novel computer vision models for satellite-based real-time vessel monitoring in support of maritime conservation efforts.

Abstract: Illegal, unreported, and unregulated (IUU) fishing poses a global threat to ocean habitats. Publicly available satellite data offered by NASA and the European Space Agency (ESA) provide an opportunity to actively monitor this activity. Effectively leveraging satellite data for maritime conservation requires highly reliable machine learning models operating globally with minimal latency. This paper introduces three specialized computer vision models designed for synthetic aperture radar (Sentinel-1), optical imagery (Sentinel-2), and nighttime lights (Suomi-NPP/NOAA-20). It also presents best practices for developing and delivering real-time computer vision services for conservation. These models have been deployed in Skylight, a real time maritime monitoring platform, which is provided at no cost to users worldwide.

Submission Number: 17