An Optical Flow SBAS Technique for Glacier Surface Velocity Extraction Using SAR Images

The pixel offset-tracking (PO) technique developed from correlation matching for use on synthetic aperture radar (SAR) images has been widely employed to monitor glacier dynamics. However, the decorrelation caused by rapid changes in a glacier surface reduces the integrity of flow velocity extraction. In this letter, we propose a novel method, termed the optical flow (OF) small baseline subset (SBAS), developed from the OF algorithm, which is defined as the apparent motion of individual pixels on the image plane. The OF algorithm can compute dense flows at the individual pixel level with a low computational cost and may serve as an alternative to PO for estimating the glacier velocity field. During processing, we selected the image pairs having short spatiotemporal baselines and calculated their offset series according to the OF algorithm. We then used an interval estimation strategy to eliminate outliers to refine stacked offsets. Finally, the least-squares method was used to calculate the displacement series for each pixel. We tested the proposed method utilizing eight advanced land observing satellite-2 (ALOS-2)/phased array type L-band synthetic aperture radar-2 (PALSAR-2) images on a temperate debris-covered glacier, the Hailuogou Glacier (HG) on the southeastern Tibetan Plateau. Compared with PO-SBAS, our method effectively improves the coverage of glacier flow velocity monitoring from 73.5% to 99.6%.