GNSS-corrected InSAR displacement time-series spanning the 2019 Ridgecrest, CA earthquakes
GNSS-corrected InSAR displacement time-series spanning the 2019 Ridgecrest, CA earthquakes
复制标题
2019 年加利福尼亚州里奇克莱斯特地震的 GNSS 校正 InSAR 位移时间序列
DOI：
10.1093/gji/ggac121
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发表时间：
2022
影响因子：
2.8
通讯作者：
Sandwell, David
中科院分区：
文献类型：
--
作者：
Guns, Katherine;Xu, Xiaohua;Bock, Yehuda;Sandwell, David
干涉合成孔径雷达（InSAR）位移时间序列是研究地球过程的一个重要工具。然而，当前时间序列处理方法的一个挑战是，当大地震发生时，它们可能在时间序列中留下尖锐的同震阶跃。这些不连续性可能导致当前的大气校正和噪声平滑算法崩溃，因为这些算法通常假设变形随时间推移是稳定的。在这里，我们的目的是纠正这一点，探索两种方法来纠正地震偏移的干涉合成孔径雷达时间序列：一个简单的差分偏移估计（SDOE）过程和多参数偏移估计（MPOE）参数时间序列反演技术。我们将这些方法应用于跨越2019年里奇克雷斯特，CA地震序列的Sentinel-1干涉图的2年时间序列。下降轨道的结果表明，SDOE方法精确地纠正只有20%的同震偏移在62个研究地点包括在我们的场景，只有部分纠正或有时过度纠正我们的研究地点的其余部分。另一方面，在我们的分析中，MPOE估计方法成功地校正了大多数场地的同震偏移。这种MPOE方法使我们能够产生干涉合成孔径雷达时间序列和数据衍生的估计变形在地震周期的每个阶段。为了更好地分离和估计干涉合成孔径雷达时间序列中的震后岩石圈形变信号，我们对干涉图进行了基于GNSS的校正。这种校正将干涉图与中值滤波的每周全球导航卫星系统位移联系起来，并消除了额外的大气伪影。我们提出了基于InSAR的估计地震后变形的里奇克雷斯特破裂，以及2年的同震校正，GNSS校正的干涉合成孔径雷达时间序列数据集周围的地区。这一经过全球导航卫星系统校正的干涉合成孔径雷达时间序列将有助于今后对地震后过程进行建模，如断裂近场的后滑、中距离的孔隙弹性变形和远场较长时间尺度的粘弹性变形。
InSAR displacement time-series are emerging as a valuable product to study a number of Earth processes. One challenge to current time-series processing methods, however, is that when large earthquakes occur, they can leave sharp coseismic steps in the time-series. These discontinuities can cause current atmospheric correction and noise smoothing algorithms to break down, as these algorithms commonly assume that deformation is steady through time. Here, we aim to remedy this by exploring two methods for correcting earthquake offsets in InSAR time-series: a simple difference offset estimate (SDOE) process and a multiparameter offset estimate (MPOE) parametric time-series inversion technique. We apply these methods to a 2-yr time-series of Sentinel-1 interferograms spanning the 2019 Ridgecrest, CA earthquake sequence. Descending track results indicate that the SDOE method precisely corrects for only 20 per cent of the coseismic offsets at 62 study locations included in our scene and only partially corrects or sometimes overcorrects for the rest of our study sites. On the other hand, the MPOE estimate method successfully corrects the coseismic offset for the majority of sites in our analysis. This MPOE method allows us to produce InSAR time-series and data-derived estimates of deformation during each phase of the earthquake cycle. In order to better isolate and estimate the signal of post-seismic lithospheric deformation in the InSAR time-series, we apply a GNSS-based correction to our interferograms. This correction ties the interferograms to median-filtered weekly GNSS displacements and removes additional atmospheric artefacts. We present InSAR-based estimates of post-seismic deformation for the area around the Ridgecrest rupture, as well as a 2-yr coseismic-corrected, GNSS-corrected InSAR time-series data set. This GNSS-corrected InSAR time-series will enable future modelling of post-seismic processes such as afterslip in the near field of the rupture, poroelastic deformation at intermediate distances and viscoelastic deformation at longer timescales in the far field.