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Landslide characteristics revealed by high-frequency seismic waves from the 2017 landslide in central Japan

Issei Doi and Takuto Maeda
Landslide characteristics revealed by high-frequency seismic waves from the 2017 landslide in central Japan
Seismological Research Letters (July 2020) Pre-Issue Publication

Abstract

The recent development of advanced seismograph networks offers us a chance to remotely detect landslide occurrences with high-frequency (> approximately 1 Hz) components. This study examined a landslide in central Japan that produced clearly detectable seismic signals at multiple seismic stations in a permanent network. Wave packets propagated with a group velocity of 3 km/s from the landslide area. Using a source location determination method with amplitude information from the high-frequency component, the source location of the wave packets was shown to be in the vicinity of the landslide with an error of 5 km. Moreover, seismograms specific to this landslide also contained a distinct impulsive phase with a source located in the vicinity of the landslide. The study demonstrated that seismic waves with a high-frequency component from landslides can be used to estimate their mechanisms as well as their locations when they are recognized by a routine seismic network.


ISSN: 0895-0695
EISSN: 1938-2057
Serial Title: Seismological Research Letters
Serial Volume: Pre-Issue Publication
Title: Landslide characteristics revealed by high-frequency seismic waves from the 2017 landslide in central Japan
Affiliation: Kyoto University, Disaster Prevention Research Institute, Kyoto, Japan
Published: 20200722
Text Language: English
Publisher: Seismological Society of America, El Cerrito, CA, United States
References: 30
Accession Number: 2020-079372
Categories: Seismology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sketch maps
N36°30'00" - N37°30'00", E137°30'00" - E139°00'00"
Secondary Affiliation: Hirosaki University, JPN, Japan
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2020, American Geosciences Institute. Abstract, Copyright, Seismological Society of America. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 202022
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