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We investigate the feasibility to align synthetic aperture radar (SAR) imagery based on a compensation for sea ice drift occurring between temporally shifted image acquisitions. The image alignment is a requirement for improving sea ice classification by combining multi-frequency SAR images acquired at different times. Images obtained at different radar frequencies provide complementary information, thus reducing ambiguities in the separation of ice types and the retrieval of sea ice parameters. For the alignment we use ice displacement vectors obtained from a sea ice drift retrieval algorithm based on pattern matching. The displacement vectors are organized on a triangular mesh and used for a piecewise affine transformation of the slave image onto the master image. In our case study we developed an alignment framework for pairs of ALOS-2 PALSAR-2 (L-band) and Sentinel-1 (C-band) images. We demonstrate several successful examples of alignment for time gaps ranging from a few hours to several days, depending on ice conditions. The data were acquired over three test sites in the Arctic: Belgica Bank, Fram Strait, and Lincoln Sea. We assess the quality of alignment using the structural similarity index (SSIM). From the displacement vectors, locations and extensions of patches of strong ice deformation are determined which allows to estimate the possible areal size of successful alignment over undeformed ice and a judgment of the expected quality for each image pair. The comprehensive assessment of hundreds of aligned L-C SAR pairs shows the potential of our method to work under various environmental conditions provided that the ice drift can be estimated reliably.

Alignment of Multi-Frequency SAR Images Acquired over Sea Ice Using Drift Compensation