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首页> 外文期刊>Journal of geophysical research. Solid earth: JGR >Independent Component Analysis and Parametric Approach for Source Separation in InSAR Time Series at Regional Scale: Application to the 2017-2018 Slow Slip Event in Guerrero (Mexico)
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Independent Component Analysis and Parametric Approach for Source Separation in InSAR Time Series at Regional Scale: Application to the 2017-2018 Slow Slip Event in Guerrero (Mexico)

机译：区域规模漫游时间序列源分离的独立分量分析与参数方法：应用于2017-2018在Guerrero（墨西哥）的慢速滑动事件

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Separating different sources of signal in Interferometric Synthetic Aperture Radar (InSAR) studies over large areas is challenging, especially between the long-wavelength changes of atmospheric conditions and tectonic deformations, both correlated to elevation. In this study, we focus on the 2017-2018 slow slip event (SSE) in the Guerrero state (Mexico) where (1) the permanent GPS network has a low spatial density (less than 30 stations in an area of 300 x 300 km) with uneven distribution; (2) the tropospheric phase delays can be as high as 20 cm of apparent ground displacements, with a complex temporal evolution; (3) the tested global weather models fail to correct interferograms with enough accuracy (with residual tropospheric signal higher than the tectonic signal); and (4) the surface displacement caused by the seismic cycle shows complex interactions between seismic sequences and aseismic events. To extract the SSE signal from Sentinel-1 InSAR time series, we test two different approaches. The first (parametric method) consists of a least squares linear inversion, imposing a functional form for each deformation or atmospheric component. The second uses independent component analysis of the InSAR time series. We obtain time series maps of surface displacements along the radar line of sight associated with the SSE and validate these results with a comparison to GPS. Combining those two approaches, we propose a method to separate atmospheric delays and tectonic deformation on time series data not corrected from atmospheric delays. From the extracted ground deformation maps, we propose a first-order slip inversion model at the subduction interface during this SSE.
机译：在大区域的干涉性合成孔径雷达（Insar）研究中分离不同的信号源是具有挑战性的，特别是在大气条件和构造变形的长波长变化之间，两者与升降相关。在这项研究中，我们专注于Guerrero状态（墨西哥）的2017-2018慢速滑动事件（SSE），其中（1）永久性GPS网络具有低空间密度（面积300 x 300千克的车站不到30个站）分布不均匀; （2）对流层相延迟可以高达20厘米的表观地移，具有复杂的时间进化; （3）测试的全球天气模型不能纠正足够精度的干涉图（具有比构造信号高的剩余的对流层信号）; （4）由地震循环引起的表面位移显示出地震序列和抗震事件之间的复杂相互作用。要从Sentinel-1 Insar时间序列中提取SSE信号，我们测试了两种不同的方法。第一（参数法）由最小二乘线性反转组成，施加针对每个变形或大气组分的功能形式。第二种使用Insar时间序列的独立分量分析。我们沿着与SSE相关联的雷达视线沿着雷达视线的表面位移的时间序列地图，并与GPS比较验证这些结果。结合这两种方法，我们提出了一种在不校正的时间序列数据上分离大气延迟和构造变形的方法。从提取的地面变形图中，我们在该SSE期间提出了在俯冲界面处的一阶滑动反转模型。

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    Maubant L.; Pathier E.; Daout S.; Radiguet M.; Doin M-P; Kazachkina E.; Kostoglodov V; Cotte N.; Walpersdorf A.;

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    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

    Univ Oxford Dept Earth Sci COMET Oxford England;

    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

    Univ Nacl Autonoma Mexico Inst Geophys Mexico City DF Mexico;

    Univ Nacl Autonoma Mexico Inst Geophys Mexico City DF Mexico;

    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

    Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS IRD IFSTTAR Grenoble France;

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  • 中图分类 地球物理学;
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