An Adaptive Offset Tracking Method with SAR Images for Landslide Displacement Monitoring
An Adaptive Offset Tracking Method with SAR Images for Landslide Displacement Monitoring
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一种用于滑坡位移监测的SAR图像自适应偏移跟踪方法
DOI：
10.3390/rs9080830
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发表时间：
2017-08-01
期刊：
影响因子：
5
通讯作者：
Wang, Qijie
中科院分区：
文献类型：
--
作者：
Cai, Jiehua;Wang, Changcheng;Wang, Qijie
随着高分辨率合成孔径雷达(SAR)系统的发展，合成孔径雷达(SAR)偏移距跟踪方法在地表形变估计中的应用越来越受到研究者的重视。传统的归一化互相关(NCC)跟踪方法是基于规则匹配窗口的。对于不同运动特征的区域，特别是滑坡边界区域，NCC方法会产生不正确的结果。这是因为在滑坡边界区域，规则匹配窗口的像素点包括两种或两种以上的运动特征：一些像素点位移较大，另一些像素点位移较小或没有位移。这两种像素是不相关的，这导致了不准确的估计。为了提高滑坡位移估计的精度，提出了一种基于自适应匹配窗口的SAR图像偏移距跟踪方法。该方法生成一个只包含具有相似运动特征的像素的自适应匹配窗口。利用喷气推进实验室的无人机合成孔径雷达(UAVSAR)系统获取的3幅SAR图像，对位于美国科罗拉多州西南部的塌方滑坡的地表变形进行了估算。结果表明，该方法比传统的NCC方法具有更高的精度，特别是在滑坡边界区域。此外，它还可以获得更详细的滑坡边界区域的位移信息。
With the development of high-resolution Synthetic Aperture Radar (SAR) systems, researchers are increasingly paying attention to the application of SAR offset tracking methods in ground deformation estimation. The traditional normalized cross correlation (NCC) tracking method is based on regular matching windows. For areas with different moving characteristics, especially the landslide boundary areas, the NCC method will produce incorrect results. This is because in landslide boundary areas, the pixels of the regular matching window include two or more types of moving characteristics: some pixels with large displacement, and others with small or no displacement. These two kinds of pixels are uncorrelated, which result in inaccurate estimations. This paper proposes a new offset tracking method with SAR images based on the adaptive matching window to improve the accuracy of landslide displacement estimation. The proposed method generates an adaptive matching window that only contains pixels with similar moving characteristics. Three SAR images acquired by the Jet Propulsion Laboratory's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected to estimate the surface deformation of the Slumgullion landslide located in the southwestern Colorado, USA. The results show that the proposed method has higher accuracy than the traditional NCC method, especially in landslide boundary areas. Furthermore, it can obtain more detailed displacement information in landslide boundary areas.