Sea ice drift vectors extraction based on feature tracking to Sentinel-1 images
Sea ice drift is an important natural phenomenon in the Arctic,and it is important for climate research and human activities such as shipping security in the Arctic area.At present,sea ice drift products are often derived with space-borne radiometers and scatterometers with the template matching algorithm and suffer from low resolution and low accuracy.Sentinel-1 synthetic aperture radar imagery has high spatial resolution and holds great potential for deriving sea ice drift fields with high resolution and high accuracy by applying feature matching algorithms.This research compared sea ice drift results derived from four popular features including SIFT,SURF,ORB,and A-KAZE by using two pairs of Sentinel-1 Arctic sea ice SAR images.The similarities and differences between the performances of HH and HV imagery were also analyzed in terms of spatial distribution and coverage of the derived sea ice drift vectors.We proposed a filtering method combined with two published methods to identify incorrect vectors after the NNDR test with high calculation efficiency and accuracy.Finally,we evaluated the accuracy of sea ice drift vectors by comparing our derived results and DTU sea ice products with GPS data of MOSAiC buoys.Employing A-KAZE features to Sentinel-1 EW imagery can effectively derive sea ice drift fields with high spatial resolution and coverage rates.A-KAZE feature performs better than SIFT,SURF,and ORB in terms of spatial distribution and the number of vectors.Combining the vectors obtained from HH and HV polarization imagery can effectively extend the coverage of sea ice motion fields.The incorrect vector filter checks the similarity of a vector to its neighbors only if its speed or direction exceeds two times the standard deviation.It improves computational efficiency and retains more correct vectors than the two traditional methods.Validation with data of MOSAiC buoys found that the average speed error of sea ice drift vectors extracted using the proposed A-KAZE-based method was less than 0.2 km/d,and the average direction error was less than 1°.These products share a high consistency with DTU sea ice drift products obtained through employing Sentinel-1 SAR imagery but applying the template matching algorithm.However,our proposed methods presented a higher spatial coverage.This study demonstrates the potential of deriving sea ice drift vectors by applying dual-polarized Sentinel-1 SAR imagery and A-KAZE features.This approach can effectively and quickly generate sea ice drift vector fields of high spatial resolution with high spatial covering rates and high accuracy,which can serve as an accurate data source for climate research and maritime security in the Arctic.
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