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Characterization of Geohazards via Seismic and Acoustic Waves.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Characterization of Geohazards via Seismic and Acoustic Waves./
作者:	Toney, Liam.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	154 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
標題:	Geophysics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30570215
ISBN:	9798379952211

Characterization of Geohazards via Seismic and Acoustic Waves.
Toney, Liam.

Characterization of Geohazards via Seismic and Acoustic Waves. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 154 p.

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--University of Alaska Fairbanks, 2023.

.

Earth processes, such as large landslides and volcanic eruptions, occur globally and can be hazardous to life and property. Geophysics - the quantitative study of Earth processes and properties - is used to monitor and rapidly respond to these geohazards. In particular, seismoacoustics, which is the joint study of seismic waves in the solid Earth and acoustic waves in Earth's atmosphere, has been proven effective for a variety of geophysical monitoring tasks. Typically, the acoustic waves studied are infrasonic: They have frequencies less than 20 hertz, which is below the threshold of human hearing. In this dissertation, we use seismic and acoustic waves and techniques to characterize geohazards, and we examine the propagation of the waves themselves to better understand how seismoacoustic energy is transformed on its path from a given source to the measurement location. Chapter 1 provides a broad overview of seismoacoustics tailored to this dissertation. In Chapter 2, we use seismic and acoustic waves to reconstruct the dynamics of two very large, and highly similar, ice and rock avalanches occurring in 2016 and 2019 on Iliamna Volcano (Alaska). We determine their trajectories using seismic data from distant stations, demonstrating the feasibility of remote seismic landslide characterization. Chapter 3 details the application of machine learning to a rich volcano infrasound dataset consisting of thousands of explosions recorded at Yasur Volcano (Vanuatu) over six days in 2016. We automatically generate a labeled catalog of infrasound waveforms associated to two different locations in Yasur's summit crater, and use this catalog to test different strategies for transforming the waveforms prior to classification model input. In Chapter 4, we use the coupling of atmospheric waves into the Earth to leverage a dense network of about 900 seismometers around Mount Saint Helens volcano (Washington state) as a quasi-infrasound network. We use buried explosions from a 2014 experiment as sources of infrasound. The dense spatial wavefield measurements permit detailed examination of the effects of wind and topography on infrasound propagation. Finally, in Chapter 5 we conclude with some discussion of future work and additional seismoacoustic topics.

ISBN: 9798379952211Subjects--Topical Terms:

535228
Geophysics.
Subjects--Index Terms:

Geohazards

Characterization of Geohazards via Seismic and Acoustic Waves.
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300 $a 154 p.
500 $a Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
500 $a Advisor: Fee, David.
502 $a Thesis (Ph.D.)--University of Alaska Fairbanks, 2023.
506 $a .
520 $a Earth processes, such as large landslides and volcanic eruptions, occur globally and can be hazardous to life and property. Geophysics - the quantitative study of Earth processes and properties - is used to monitor and rapidly respond to these geohazards. In particular, seismoacoustics, which is the joint study of seismic waves in the solid Earth and acoustic waves in Earth's atmosphere, has been proven effective for a variety of geophysical monitoring tasks. Typically, the acoustic waves studied are infrasonic: They have frequencies less than 20 hertz, which is below the threshold of human hearing. In this dissertation, we use seismic and acoustic waves and techniques to characterize geohazards, and we examine the propagation of the waves themselves to better understand how seismoacoustic energy is transformed on its path from a given source to the measurement location. Chapter 1 provides a broad overview of seismoacoustics tailored to this dissertation. In Chapter 2, we use seismic and acoustic waves to reconstruct the dynamics of two very large, and highly similar, ice and rock avalanches occurring in 2016 and 2019 on Iliamna Volcano (Alaska). We determine their trajectories using seismic data from distant stations, demonstrating the feasibility of remote seismic landslide characterization. Chapter 3 details the application of machine learning to a rich volcano infrasound dataset consisting of thousands of explosions recorded at Yasur Volcano (Vanuatu) over six days in 2016. We automatically generate a labeled catalog of infrasound waveforms associated to two different locations in Yasur's summit crater, and use this catalog to test different strategies for transforming the waveforms prior to classification model input. In Chapter 4, we use the coupling of atmospheric waves into the Earth to leverage a dense network of about 900 seismometers around Mount Saint Helens volcano (Washington state) as a quasi-infrasound network. We use buried explosions from a 2014 experiment as sources of infrasound. The dense spatial wavefield measurements permit detailed examination of the effects of wind and topography on infrasound propagation. Finally, in Chapter 5 we conclude with some discussion of future work and additional seismoacoustic topics.
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650 4 $a Geophysics. $3 535228
650 4 $a Geology. $3 516570
653 $a Geohazards
653 $a Earth processes
653 $a Seismic waves
653 $a Acoustic waves
653 $a Seismoacoustics
690 $a 0373
690 $a 0467
690 $a 0372
710 2 $a University of Alaska Fairbanks. $b Geosciences. $3 3437612
773 0 $t Dissertations Abstracts International $g 85-01B.
790 $a 0006
791 $a Ph.D.
792 $a 2023
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30570215