https://www.glaciology.net/tags/deep-learning/ Recent content in Deep Learning on Aslak Grinsted Hugo en-us Sat, 24 Oct 2026 00:00:00 +0000 https://www.glaciology.net/studentproject/2026/ml_iceflow/ Sat, 24 Oct 2026 00:00:00 +0000 https://www.glaciology.net/studentproject/2026/ml_iceflow/ <p>Satellites now map the surface velocity of the ice sheets in remarkable detail, and we have good maps of ice geometry, surface conditions and climate. Could a neural network learn the relationship between them, and predict how fast the ice flows directly from what we observe?</p> <p>In this project, you will train a deep neural network, for example a U-Net, to predict observed ice velocities from inputs such as surface elevation, ice thickness, whether the ice is grounded or floating, temperature, melt rates, and perhaps satellite imagery. Velocity products such as ESA&rsquo;s Climate Change Initiative (CCI) and ITS_LIVE, combined with frequently updated surface elevations from satellite altimetry, make it possible to follow how both geometry and flow change through time. Neural networks have been used to emulate ice-flow models, but learning ice flow directly from observations is much less explored.</p>