The exploitation of ever increasing Interferometric Synthetic Aperture Radar (InSAR) data sets to monitor the Earth's surface deformation is an important goal of today's geodesy. In this study our observations consist of deformations along the Line‐Of‐Sight direction of the satellite. Our observations are the result of the combination of a multitude of sources (either volcano‐tectonic or nontectonic deformation). In most cases, we are facing a Blind source separation (BSS) problem. Natural approaches to tackle BSS problems are multivariate statistical techniques that attempt to decompose the data set into a limited number of statistically independent sources, under the assumption that the different physical mechanisms contributing to the observations have independent footprints in space and/or time. We show the capabilities of a variational Bayesian independent component analysis (vbICA) algorithm in dealing with synthetic InSAR time series and compare it to the commonly used FastICA algorithm. We explore the effectiveness of the spatial and temporal mode decompositions. We apply vbICA on data relative to the San Joaquin Valley and the Central San Andreas fault (CSAF), California, spanning the time range 2015/03/01–2019/07/14. The proposed approach likely isolates the contribution of shallow and deep aquifers to the surface deformation as well as the elastic and inelastic deformation. We present a 1‐dimensional compaction estimation of the elastic and inelastic storage coefficients adopting a formalism that takes into account the last century water level history. Concerning the CSAF, the algorithm helps separating tectonic loading from seasonal behavior concentrated in the Quaternary sediments of the Salinas Valley.

中文翻译：

---

InSAR位移时间序列的变分贝叶斯独立分量分析及其在美国中部加州的应用

利用不断增长的干涉合成孔径雷达（InSAR）数据集来监视地球表面变形是当今大地测量学的重要目标。在这项研究中，我们的观察包括沿卫星视线方向的变形。我们的观察结果是多种来源（火山构造或非构造变形）相结合的结果。在大多数情况下，我们面临盲源分离（BSS）问题。解决BSS问题的自然方法是多变量统计技术，这些技术试图在有助于观测的不同物理机制在空间和/或时间上具有独立足迹的假设下，将数据集分解为数量有限的统计独立来源。我们展示了变分贝叶斯独立分量分析（vbICA）算法在处理合成InSAR时间序列中的功能，并将其与常用的FastICA算法进行了比较。我们探索时空模式分解的有效性。我们将vbICA应用于与加利福尼亚州圣华金河谷和圣安德烈亚斯中部断层（CSAF）有关的数据，时间跨度为2015/03 / 01–2019 / 07/14。所提出的方法可能隔离浅层和深层含水层对表面变形以及弹性变形和非弹性变形的贡献。我们采用考虑了上个世纪水位历史的形式主义，给出了弹性和非弹性存储系数的一维压缩估计。关于CSAF，