IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method-Reference-Cited by-同舟云学术

IPIML: A Deep-Scan Earthquake Detection and Location Workflow Integrating Pair-Input Deep Learning Model and Migration Location Method

Published:2023 Issue: Volume:61 Page:1-9
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Mohammadigheymasi Hamzeh¹^ORCID,Shi Peidong²^ORCID,Tavakolizadeh Nasrin³^ORCID,Xiao Zhuowei⁴^ORCID,Mousavi S. Mostafa⁵^ORCID,Matias Luis⁶^ORCID,Pourvahab Mehran³^ORCID,Fernandes Rui¹^ORCID

Affiliation:

1. Departamento de Informática, Instituto Dom Luiz (IDL) and the Space & Earth Geodetic Analysis Laboratory (SEGAL), Universidade da Beira Interior (UBI), Covilhã, Portugal

2. Swiss Seismological Service, Zürich, ETH-Zürich, Switzerland

3. Instituto de Telecomunicações and the Departamento de Informática, University of Beira Interior, Covilhã, Portugal

4. Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China

5. Department of Geophysics, University of Stanford, Stanford, CA, USA

6. Instituto Dom Luiz, Faculdade de Ciencias, Universidade de Lisboa, Lisbon, Portugal

Funder

European Union

Instituto Dom Luiz (IDL) Project

Collaboratory for Geosciences

Fundação para a Ciência e a Tecnologia (FCT) in the content of the Project SHAZAM “Sismicidade e Perigosidade da Margem Atlântica sub-Saariana,”

FEDER-COMPETE/POCI 2020, FCT

Instituto de Telecomunicações

ERANET Cofund GEOTHERMICA

exploration subsidy of the Swiss Federal Office of Energy for the EGS geothermal project in Haute-Sorne, canton of Jura

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10177744.pdf?arnumber=10177744

Reference32 articles.

1. QuakeFlow: a scalable machine-learning-based earthquake monitoring workflow with cloud computing

2. LOC-FLOW: An End-to-End Machine Learning-Based High-Precision Earthquake Location Workflow

3. Building Precise Local Submarine Earthquake Catalogs via a Deep-Learning-Empowered Workflow and its Application to the Challenger Deep

4. hypoDD—A program to compute double-difference hypocenter locations (hypoDD version 1.0-03/2001);waldhauser,2001

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