Complete three-dimensional near-field surface displacements from imaging geodesy techniques applied to the 2016 Kumamoto earthquake
Complete three-dimensional near-field surface displacements from imaging geodesy techniques applied to the 2016 Kumamoto earthquake
复制标题
应用于 2016 年熊本地震的成像大地测量技术的完整三维近场表面位移
DOI：
10.1016/j.rse.2019.111321
复制
发表时间：
2019-10-01
影响因子：
13.5
通讯作者：
Chen, Yunguo
中科院分区：
文献类型：
--
作者：
He, Ping;Wen, Yangmao;Chen, Yunguo
近年来成像大地测量技术的发展，是一种高空间分辨率、大范围覆盖的先进技术，使研究人员能够以较低的人力成本获得多次高质量的地表位移估算，从而提高地质灾害监测和治理的能力。用于推导位移估计的成像大地测量中的不同来源（例如雷达、光学和 LiDAR 传感器）和分析方法（例如差分干涉合成孔径雷达 DInSAR、多孔径 InSAR、像素偏移跟踪和迭代最近点 ICP）具有独特的优点和缺点。然而，这些数据源和方法在构建三维（3D）变形图（尤其是近场）方面的固有差异仍然知之甚少，需要进一步讨论。在本研究中，我们获取了 2016 年熊本地震的三对 ALOS-2 带状图模式图像、两对 Sentinel-1 TOPS 模式图像以及震前和震后 LiDAR 数据，利用各种成像大地测量技术和不同类型的图像信息（即 SAR 相位数据、SAR 振幅数据和 LiDAR 点云数据）来探索 3D 近场位移。我们的结果表明，每种图像类型都能够独立生成 2016 年熊本地震的高质量 3D 变形图，故障精度为
The recent development of imaging geodesy, an advanced technique with a high spatial resolution and large-scale coverage, has enabled researchers to obtain multiple high-quality surface displacement estimates at low labor-cost, thereby improving the capability to monitor and manage geological disasters. The different sources (e.g., radar, optical and LiDAR sensors) and analysis approaches (e.g., differential interferometric synthetic aperture radar, DInSAR; multiple-aperture InSAR; pixel offset tracking; and iterative closest point, ICP) in imaging geodesy used to derive displacement estimates have unique benefits and drawbacks. However, the inherent differences among these data sources and methods in the construction of three-dimensional (3D) deformation maps, particularly in the near field, remain poorly understood and require further discussion. In this study, we acquired three pairs of ALOS-2 stripmap mode images, two pairs of Sentinel-1 TOPS mode images and pre- and post-event LiDAR data for the 2016 Kumamoto earthquake to explore the 3D near-field displacements using various imaging geodesy techniques with different types of image information, i.e., SAR phase data, SAR amplitude data and LiDAR point cloud data. Our results show that each image type is independently capable of producing a high-quality 3D deformation map for the 2016 Kumamoto earthquake with an on-fault accuracy of