Intercomparison of Sea Ice Tracking Algorithms from Multifrequency SAR Images in the Arctic

In this study, we assess the performance of the three state-of-the-art ice drift retrieval algorithms for Synthetic aperture radar (SAR) images. The algorithms were selected by their difference in underlying technique to reveal their advantages and limitations based on C- and X-band data in the Arctic. The results suggest that area-based algorithms are applicable in most cases, while feature-tracking algorithm demonstrates better precision but with fewer produced drift vectors. The hybrid algorithm provides the best data density compared to the other two algorithms but suffers from generating artificial vectors in the case of strong ice speed gradients such as at the edge between fast and drift ice.