AI developed to monitor changes to the globally important Thwaites Glacier
Scientists have developed artificial intelligence techniques to track the development of crevasses—or fractures—on the Thwaites Glacier Ice Tongue in west Antarctica.
A team of scientists from the University of Leeds and University of Bristol have adapted an AI algorithm originally developed to identify cells in microscope images to spot crevasses forming in the ice from satellite images. Crevasses are indicators of stresses building-up in the glacier.
Thwaites is a particularly important part of the Antarctic Ice Sheet because it holds enough ice to raise global sea levels by around 60 centimeters and is considered by many to be at risk of rapid retreat, threatening coastal communities around the world.
Use of AI will allow scientists to more accurately monitor and model changes to this important glacier.
Published today (Monday, January 9) in the journal Nature Geoscience, the research focused on a part of the glacier system where the ice flows into the sea and begins to float. Where this happens is known as the grounding line and it forms the start of the Thwaites Eastern Ice Shelf and the Thwaites Glacier Ice Tongue, which is also an ice shelf.
Despite being small in comparison to the size of the entire glacier, changes to these ice shelves could have wide-ranging implications for the whole glacier system and future sea-level rise.
Scientists have mapped the crevasses on the Thwaites Glacier Ice Tongue through time using deep learning. This new research marks a change in the way in which the structural and dynamic properties of ice shelves can be investigated. Credit: Trystan Surawy-Stepney, University of Leeds
Crevasses on Antarctic ice shelves change the material properties of the ice and influence their flow-speed. Research shows this coupling to be relevant but more complicated than previously thought for the Thwaites Glacier Ice Tongue. Credit: Dr Anna Hogg, University of Leeds
Scientists have used radar imagery from the European Space Agency’s Sentinel-1 satellites to measure flow speed of the Thwaites Glacier Ice Tongue (shown) and analyse its structural integrity using deep learning. Credit: Benjamin J. Davison, University of Leeds