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  4. 中国科学院地球与行星物理重点实验室
IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method

文献类型：期刊论文

作者Mohammadigheymasi, Hamzeh2,3; Shi, Peidong8; Tavakolizadeh, Nasrin1,7; Xiao, Zhuowei6; Mousavi, S. Mostafa5; Matias, Luis4; Pourvahab, Mehran1,7; Fernandes, Rui2,3
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2023
卷号61页码:9
ISSN号0196-2892
关键词Earthquake detection and location pair-input deep learning (PIDL) waveform migration location (MIL) method
DOI10.1109/TGRS.2023.3293914
英文摘要Optimized deep learning (DL)-based workflows can improve the efficiency and accuracy of earthquake detection and location processes. This article introduces a six-step automated event detection, phase association, and earthquake location workflow, which integrates the state-of-the-art pair-input DL (PIDL) model and waveform migration location methods [integrated PIDL and MIL (IPIML)]. Applying IPIML on an 18-month dataset of Ghana Digital Seismic Network (GHSDN) recorded from 2012 to 2014, a catalog with 461 events is automatically obtained. Compared to other DL catalogs obtained using EQTransformer (EQT) and Siamese EQT (S-EQT), the seismic event clusters in the IPIML catalog focus more on tectonically active regions or known seismogenic source areas and show a consistent depth distribution. The compiled catalog is 6.3x larger than the reported catalog obtained by applying EQT with the default settings, indicating the importance of optimization and hyperparameter tuning when applying DL models. As a result, a previously unknown seismogenic fault with a clear spatial trend has been identified using the new IPIML catalog, which provides more insights into the fault activities and seismic hazards in the region. The IPIML codes and datasets are available at the GitHub repository https://github.com/SigProSeismology/IPIML.git, contributing to the geoscience community.
资助项目European Union (EU) ; Collaboratory for Geosciences (C4G)[PINFRA/22151/2016] ; Fundacao para a Ciencia e a Tecnologia (FCT)[PTDC/CTA/GEO/31475/2017] ; Fundacao para a Ciencia e a Tecnologia (FCT)[POCI-01-0145-FEDER-031475] ; FEDER-COMPETE/POCI 2020, FCT ; Instituto de Telecomunicacoes - FCT/MCTES ; EU funds[UIDB/50008/2020] ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission[200320-4001] ; Swiss Federal Office of Energy[MF-021-GEO-ERK] ; Instituto Dom Luiz (IDL) Project[UIDB/50019/2020]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:001045724900007
资助机构European Union (EU) ; European Union (EU) ; Collaboratory for Geosciences (C4G) ; Collaboratory for Geosciences (C4G) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; FEDER-COMPETE/POCI 2020, FCT ; FEDER-COMPETE/POCI 2020, FCT ; Instituto de Telecomunicacoes - FCT/MCTES ; Instituto de Telecomunicacoes - FCT/MCTES ; EU funds ; EU funds ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; Swiss Federal Office of Energy ; Swiss Federal Office of Energy ; Instituto Dom Luiz (IDL) Project ; Instituto Dom Luiz (IDL) Project ; European Union (EU) ; European Union (EU) ; Collaboratory for Geosciences (C4G) ; Collaboratory for Geosciences (C4G) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; FEDER-COMPETE/POCI 2020, FCT ; FEDER-COMPETE/POCI 2020, FCT ; Instituto de Telecomunicacoes - FCT/MCTES ; Instituto de Telecomunicacoes - FCT/MCTES ; EU funds ; EU funds ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; Swiss Federal Office of Energy ; Swiss Federal Office of Energy ; Instituto Dom Luiz (IDL) Project ; Instituto Dom Luiz (IDL) Project ; European Union (EU) ; European Union (EU) ; Collaboratory for Geosciences (C4G) ; Collaboratory for Geosciences (C4G) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; FEDER-COMPETE/POCI 2020, FCT ; FEDER-COMPETE/POCI 2020, FCT ; Instituto de Telecomunicacoes - FCT/MCTES ; Instituto de Telecomunicacoes - FCT/MCTES ; EU funds ; EU funds ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; Swiss Federal Office of Energy ; Swiss Federal Office of Energy ; Instituto Dom Luiz (IDL) Project ; Instituto Dom Luiz (IDL) Project ; European Union (EU) ; European Union (EU) ; Collaboratory for Geosciences (C4G) ; Collaboratory for Geosciences (C4G) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; Fundacao para a Ciencia e a Tecnologia (FCT) ; FEDER-COMPETE/POCI 2020, FCT ; FEDER-COMPETE/POCI 2020, FCT ; Instituto de Telecomunicacoes - FCT/MCTES ; Instituto de Telecomunicacoes - FCT/MCTES ; EU funds ; EU funds ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; DEEP project through the ERANET Cofund GEOTHERMICA from the European Commission ; Swiss Federal Office of Energy ; Swiss Federal Office of Energy ; Instituto Dom Luiz (IDL) Project ; Instituto Dom Luiz (IDL) Project
源URL[http://ir.iggcas.ac.cn/handle/132A11/111423]  
专题地质与地球物理研究所_中国科学院地球与行星物理重点实验室
通讯作者Mohammadigheymasi, Hamzeh
作者单位1.Univ Beira Interior, Inst Telecomunicacoes, P-6200506 Covilha, Portugal
2.Univ Beira Interior UBI, Space & Earth Geodet Anal Lab SEGAL, Dept Informat, P-6200506 Covilha, Portugal
3.Univ Beira Interior UBI, Inst Dom Luiz IDL, P-6200506 Covilha, Portugal
4.Univ Lisbon, Inst Dom Luiz, Fac Ciencias, P-1749016 Lisbon, Portugal
5.Stanford Univ, Dept Geophys, Stanford, CA 94305 USA
6.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Earth & Planetary Phys, Beijing 100045, Peoples R China
7.Univ Beira Interior, Dept Informat, P-6200506 Covilha, Portugal
8.Swiss Fed Inst Technol, Swiss Seismol Serv, CH-8092 Zurich, Switzerland
推荐引用方式
GB/T 7714		 Mohammadigheymasi, Hamzeh,Shi, Peidong,Tavakolizadeh, Nasrin,et al. IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2023,61:9.
APA Mohammadigheymasi, Hamzeh.,Shi, Peidong.,Tavakolizadeh, Nasrin.,Xiao, Zhuowei.,Mousavi, S. Mostafa.,...&Fernandes, Rui.(2023).IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61,9.
MLA Mohammadigheymasi, Hamzeh,et al."IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023):9.

入库方式： OAI收割

来源：地质与地球物理研究所

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