Sea Ice Modeling and Data Assimilation (SIMDA)

An ONR-funded MURI on the
"Integrated Foundations of Sensing, Modeling, and Data Assimilation for Sea Ice Prediction"

Sea ice dynamics via regularized optimal transport

31 Aug 2020 - Bohan


In Parno et al. (2019), we introduced a new way of estimating ice motion from satellite imagery using concepts from optimal transport. The idea is to treat images as probability distributions and to leverage efficient regularized optimal transport algorithms to find a distance-minimizing transformation between images on subsequent days. From the transformation we can extract distances, velocities, and strains.