Computational techniques used to study object motion and deformation often face challenges in detecting small shifts obscured by observational noise. In sea ice, the understanding of fundamental phenomena related to dynamics is a key for increasing the predictive power of models used to analyze different scales. 

In a new research, Matias Uusinoka, Jari Haapala and Arttu Polojärvi introduced a new approach that accurately determines deformation in noisy observational data. This enables an exceptionally detailed representation of sea ice deformation from radar images.  Their work results in a fully open-source tool.

A follow-up article is in review, check it out: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-311/