气候变化领域集成服务门户(CCPortal): Locating Spatial Changes of Seismic Scattering Property by Sparse Modeling of Seismic Ambient Noise Cross-Correlation Functions: Application to the 2008 Iwate-Miyagi Nairiku (Mw 6.9), Japan, Earthquake

CCPortal

DOI	10.1029/2019JB019307
	Locating Spatial Changes of Seismic Scattering Property by Sparse Modeling of Seismic Ambient Noise Cross-Correlation Functions: Application to the 2008 Iwate-Miyagi Nairiku (Mw 6.9), Japan, Earthquake
	Hirose T.; Nakahara H.; Nishimura T.; Campillo M.
发表日期	2020
ISSN	21699313
卷号	125 期号:6
英文摘要	Locating change regions of seismic velocities and seismic scattering properties associated with volcanic activities and earthquakes is important for structural monitoring. To increase such applications, we propose to use sparse modeling to estimate spatial distributions of seismic scattering property changes. The sparse modeling is an inversion technique that enables us to estimate model parameters from a small data set with sparsity condition such as ℓ1 norm regularization. We apply this technique to seismic ambient noise cross-correlation functions from 17 Hi-net stations around the epicenter of the 2008 Iwate-Miyagi Nairiku, Japan, earthquake (Mw=6.9). We compute waveform decoherences at the 0.5–1 Hz band and invert the waveform decoherences for the spatial distributions of seismic scattering property changes. Just after the main shock, the largest change occurred at the south of the epicenter, and the maximum change of the scattering coefficient in this region is estimated to be 0.032 km−1. The result from an ordinary linear least squares inversion with the ℓ2 norm regularization is almost consistent with that from the sparse modeling. Moreover, we confirm the superiority of sparse modeling in imaging with smaller data sets. Only five seismic stations that are deployed near the epicenter so as to surround the change regions are necessary to retrieve the result from 17 stations. On the other hand, in the case of the ℓ2 norm regularization, we need at least 15 stations. The sparse modeling will be helpful to estimate the spatial distribution of seismic scattering property changes from a small data set. ©2020. American Geophysical Union. All Rights Reserved.
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187817
作者单位	National Research Institute for Earth Science and Disaster Resilience, Tsukuba, Japan; Department of Geophysics, Graduate School of Science, Tohoku University, Sendai, Japan; University Grenoble Alpes, CNRS, ISTerre, Grenoble, France
推荐引用方式 GB/T 7714	Hirose T.,Nakahara H.,Nishimura T.,et al. Locating Spatial Changes of Seismic Scattering Property by Sparse Modeling of Seismic Ambient Noise Cross-Correlation Functions: Application to the 2008 Iwate-Miyagi Nairiku (Mw 6.9), Japan, Earthquake[J],2020,125(6).
APA	Hirose T.,Nakahara H.,Nishimura T.,&Campillo M..(2020).Locating Spatial Changes of Seismic Scattering Property by Sparse Modeling of Seismic Ambient Noise Cross-Correlation Functions: Application to the 2008 Iwate-Miyagi Nairiku (Mw 6.9), Japan, Earthquake.Journal of Geophysical Research: Solid Earth,125(6).
MLA	Hirose T.,et al."Locating Spatial Changes of Seismic Scattering Property by Sparse Modeling of Seismic Ambient Noise Cross-Correlation Functions: Application to the 2008 Iwate-Miyagi Nairiku (Mw 6.9), Japan, Earthquake".Journal of Geophysical Research: Solid Earth 125.6(2020).