Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges. Seals from space: automated Antarctic ecosystem monitoring via high-resolution satellite imagery The Antarctic is constantly evolving as the ecosystem recovers from past exploitation (e.g. whaling, seal harvesting), adapts to climate change, and responds to current anthropogenic impacts including fishing (krill and Patagonian toothfish), shipping and tourism. Due to its vastness, relatively little is known about the ecology of the region and its species, and how best to mitigate and control anthropogenic impacts in this region. Traditional field methods are costly and limited in geographical extent due to areas of interest being difficult to access by ships. Remote sensing provides a low-cost, non-invasive method that can be used for ecological monitoring. The overall aim of the challenge was to create an automated system for classifying sea ice and mapping seals which can then be used to transform the satellite raster images into images with vectorised features of ice and seals. Using these two outputs (seal counts and ice classification/environmental features) we can explore ecological questions such as what habitat features do seal prefer and how is the habitat changing over time. This report presents the outputs of a week-long collaboration between the Alan Turing Institute and the British Antarctic Survey (BAS), to scope an automated system to classify sea ice, count seals, and explore the environmental factors influencing seal density.