This article considers the application of two dense coregistration algorithms to the estimation of ice flow. These algorithms estimate displacements at each pixel of the image and can be applied to pairs of radar, optical and radar/optical images. This flexibility combined with the dense estimation should improve both spatial and temporal resolutions of glacier displacement maps. Several tests are carried out on Sentinel-1 and Sentinel-2 images on Totten glacier in Antarctica. We assess the reliability of the considered algorithms by applying them to real and emulated pairs of images based on displacement fields previously estimated in the literature.
This article proposes a method based on the temporal closure of the displacement measurement's network. The aim is to extract short-term glacier velocities and to use data redundancy to reject outliers and reduce uncertainty. By using all the available displacement measurements, we retrieve a displacement time series between consecutive observation dates by means of an inversion. The proposed inversion method is an Iterative Weighted Least Square (IWLS) with a regularization on the discrete derivative of displacements. We apply our method to a glaciers velocity data-set covering Fox Glacier in the Southern Alps of New Zealand.
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