Detecting imminent eruptive activity at Mt Etna, Italy, in 2007-2008 through pattern classification of volcanic tremor data
Detecting imminent eruptive activity at Mt Etna, Italy, in 2007-2008 through pattern classification of volcanic tremor data
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DOI：
10.1016/j.jvolgeores.2010.11.019
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发表时间：
2011-02-01
影响因子：
2.9
通讯作者：
Behncke, B.
中科院分区：
文献类型：
--
作者：
Langer, H.;Falsaperla, S.;Behncke, B.
火山监测的目的是在危险活动之前识别仪器可观测参数的变化，以便向政府当局发出警报。在这些参数中，地震资料，特别是火山震动资料起着关键作用。最近的大爆发，如2008年的Okmok（阿留申群岛）和Chaiten（智利），以及在埃特纳火山（意大利）发生的许多较小的事件，都表明地震前兆活动的周期可能很短（只有几个小时），这就需要有效的近在线自动数据处理。本文提出了一种基于自组织图和模糊聚类分析的天气模式分类分析方法，并将其应用于2007-2008年埃特纳火山一系列阵发性喷发事件和一次侧面喷发期间记录的火山震颤数据。总共分析了8集；在其中的6次中，在火山爆发活动开始前9小时就发现了火山动态状态的重大变化，这远远早于经典分析中火山震颤幅度和频谱含量的变化。在两种情况下，状态转换是
Volcano monitoring aims at the recognition of changes in instrumentally observable parameters before hazardous activity in order to alert governmental authorities. Among these parameters seismic data in general and volcanic tremor in particular play a key role. Recent major explosive eruptions such as Okmok (Aleutians) and Chaiten (Chile) in 2008 and numerous smaller events at Mt Etna (Italy), have shown that the period of premonitory seismic activity can be short (only a few hours), which entails the necessity of effective automatic data processing near on-line. Here we present a synoptic pattern classification analysis based on Self Organizing Maps and Fuzzy Cluster Analysis which is applied to volcanic tremor data recorded during a series of paroxysmal eruptive episodes and a flank eruption at Etna in 2007-2008. In total, eight episodes were analyzed; in six of these significant changes in the dynamic regime of the volcano were detected up to 9 h prior to the onset of eruptive activity, and long before changes in volcanic tremor amplitude and spectral content became evident in classical analysis. In two cases, the state transition was