气候变化领域集成服务门户(CCPortal): Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano

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DOI	10.1029/2019GL085523
	Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano
	Ren C.X.; Peltier A.; Ferrazzini V.; Rouet-Leduc B.; Johnson P.A.; Brenguier F.
发表日期	2020
ISSN	0094-8276
卷号	47 期号:3
英文摘要	Volcanic tremor is key to our understanding of active magmatic systems, but due to its complexity, there is still a debate concerning its origins and how it can be used to characterize eruptive dynamics. In this study we leverage machine learning techniques using 6 years of continuous seismic data from the Piton de la Fournaise volcano (La Réunion island) to describe specific patterns of seismic signals recorded during eruptions. These results unveil what we interpret as signals associated with various eruptive dynamics of the volcano, including the effusion of a large volume of lava during the August–October 2015 eruption as well as the closing of the eruptive vent during the September–November 2018 eruption. The machine learning workflow we describe can easily be applied to other active volcanoes, potentially leading to an enhanced understanding of the temporal and spatial evolution of volcanic eruptions. © 2020. The Authors.
英文关键词	Machine learning; Seismic waves; Seismology; Structural geology; Active volcanoes; Eruptive dynamics; Machine learning techniques; Magmatic systems; Piton de la Fournaise volcano; Seismic signatures; Temporal and spatial evolutions; Volcanic eruptions; Volcanoes; machine learning; seismic data; volcanic eruption; volcano; Piton de la Fournaise
语种	英语
来源期刊	Geophysical Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/170796
作者单位	Space Data Science and Systems Group, Los Alamos National Laboratory, Los Alamos, NM, United States; Geophysics Group, Los Alamos National Laboratory, Los Alamos, NM, United States; Université de Paris, Institut de physique du globe de Paris, CNRS, Paris, France; Observatoire volcanologique du Piton de la Fournaise, Institut de physique du globe de Paris, La Plaine des Cafres, France; ISterre, Université Grenoble Alpes, Gières, France
推荐引用方式 GB/T 7714	Ren C.X.,Peltier A.,Ferrazzini V.,et al. Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano[J],2020,47(3).
APA	Ren C.X.,Peltier A.,Ferrazzini V.,Rouet-Leduc B.,Johnson P.A.,&Brenguier F..(2020).Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano.Geophysical Research Letters,47(3).
MLA	Ren C.X.,et al."Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano".Geophysical Research Letters 47.3(2020).