Outlet glaciers of ice sheets are the primary means of transporting ice from the interior to the oceans, and their flow velocity is one control that determines the mass balance of ice sheets. Estimates of ice velocities, particularly for remote areas, are commonly based on satellite remote-sensing data. As radar-based systems emit energy at frequencies high enough to penetrate clouds, they can record backscatter signals from surfaces throughout the year. Radar data, which are collected with repeat-pass spaceborne platforms, are therefore good for extracting ice velocities using interferometry for slow-moving ice and the cross-correlation techniques for fast-moving ice. Here, we present an improvement on the cross-correlation technique that enables independent quality checks and enhances the spatial extent of the derived velocity fields. Filtering of ESA European remote sensing satellite scenes, based on a Butterworth high-pass spatial-frequency filter, focuses the cross-correlation technique on smaller, movable surface features, instead of large fixed features. It also allows a nonregional culling based on the signal-to-noise ratio of the velocities, with the effect of increasing the coverage of robust velocity estimates.
['R. de Lange', 'Adrian Luckman', 'Tavi Murray']
Improvement of Satellite Radar Feature Tracking for Ice Velocity Derivation by Spatial Frequency Filtering