High-Resolution Sea Ice Motion Estimation With Optical Flow Using Satellite Spectroradiometer Data

The purpose of this paper is twofold: 1) to propose an approach based on optical flow for the estimation of sea ice motion as an accurate, dense, and computationally efficient alternative to state-of-the-art pattern matching approaches and 2) to investigate the potential of moderate resolution imaging spectroradiometer (MODIS) optical satellite data for combined daily and high-resolution motion estimation. A series of MODIS image pairs for a selected region in Arctic Ocean is employed, and sparse pairwise correspondences between nonrigid patches are calculated. An edge-preserving sparse-to-dense interpolation is applied followed by variational energy minimization to compute the final optical flow. A state-of-the-art multiresolution pattern matching method based on phase correlation and normalized cross correlation is also implemented and evaluated for comparison. Thorough experimentation with different settings of input data preprocessing as well as varying scales of motion is performed. The derived motion vectors are compared with coarser resolution operational sea ice motion vector products from combined buoy and microwave satellite data. The proposed optical flow approach clearly outperforms the pattern matching method in most cases, both in terms of accuracy and motion vector consistency. The estimated motion vectors from the MODIS images highly correlate with the operational vector products. In addition, MODIS provides a vector field with spatial resolution two orders of magnitude higher than the operational products that are able to detect significantly smaller sea ice drifts.