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A computationally efficient, open-source feature-tracking algorithm, calledORB, is adopted and tuned for sea ice drift retrieval from Sentinel-1 SAR (Synthetic Aperture Radar) images. The most suitable setting and parameter values have been found usingfour Sentinel-1 image pairs representative of sea ice conditions betweenGreenland and Severnaya Zemlya during winter and spring.The performance of the algorithm is compared to two other feature-trackingalgorithms, namely SIFT (Scale-Invariant Feature Transform) and SURF (Speeded-Up RobustFeatures). Having been applied to 43 test image pairs acquired over Fram Strait and the north-east ofGreenland, the tuned ORB (Oriented FAST and Rotated BRIEF) algorithm produces the highest number ofvectors (177 513, SIFT: 43 260 and SURF: 25 113), while beingcomputationally most efficient (66 s, SIFT: 182 s and SURF: 99 s per imagepair using a 2.7 GHz processor with 8 GB memory). For validation purposes,314 manually drawn vectors have been compared with the closest calculatedvectors, and the resulting root mean square error of ice drift is 563 m. Alltest image pairs show a significantly better performance of the HV (horizontal transmit, vertical receive) channeldue to higher informativeness. On average, around four times as many vectorshave been found using HV polarization. All software requirements necessaryfor applying the presented feature-tracking algorithm are open source toensure a free and easy implementation

Open-source feature-tracking algorithm for sea ice drift retrieval from Sentinel-1 SAR imagery