光流
像素
地质学
合成孔径雷达
偏移量(计算机科学)
冰川
去相关
全球导航卫星系统增强
干涉合成孔径雷达
遥感
大地测量学
人工智能
计算机科学
计算机视觉
全球导航卫星系统应用
地貌学
图像(数学)
全球定位系统
电信
程序设计语言
作者
Yin Fu,Bo Zhang,Guoxiang Liu,Rui Zhang,Qiao Liu,Yuanxin Ye
标识
DOI:10.1109/lgrs.2022.3200422
摘要
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 optical flow 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 ALOS-2/PALSAR-2 images on a temperate debris-covered glacier, the Hailuogou Glacier 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%.
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