Numerous glacier velocity observations, derived from spaceborne imagery, are available online, but it remains difficult to analyze them because they are measured with different temporal baselines, by various sensors. In… Click to show full abstract
Numerous glacier velocity observations, derived from spaceborne imagery, are available online, but it remains difficult to analyze them because they are measured with different temporal baselines, by various sensors. In this study, we propose a novel formulation of the temporal closure to fuse multitemporal multisensor velocity observations without prior information on the displacement behavior and the data uncertainty. We establish a system of linear equations between combinations of displacement observations and fractions of estimated displacements. The proposed approach provides a velocity time-series with a regular and optimal temporal sampling, the latter representing a compromise between the temporal resolution and the signal-to-noise ratio. The proposed approach is first evaluated on synthetic datasets and second on Sentinel-2 and Venus velocity observations over the Fox glacier in New Zealand. The results show the intra-annual variability of Fox glacier surface velocity with a reduced uncertainty and complete temporal coverage.
               
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