Real-time Seismic Amplitude Measurement (RSAM): a volcano monitoring and prediction tool

Endo, Elliot T.; Murray, Thomas L.

doi:10.1007/bf00298154

Cited by 279 publications

(161 citation statements)

References 12 publications

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“…4g). The RSAM counts are believed to be related to the transport of magma to the surface (Endo and Murray 1991). The RSAM counts here exhibit a consecutive two-pulse pattern that is similar to the variations observed in R1.6Mx (Fig.…”

Section: Long-term Variations In Thermal Data and Stage Segmentation supporting

confidence: 71%

Himawari-8 infrared observations of the June–August 2015 Mt Raung eruption, Indonesia

Kaneko

Takasaki

Maeno

et al. 2018

Earth Planets Space

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Volcanic activity involves processes that can change over short periods of time, which are sometimes closely related to the eruptive mode or the timing of its transitions. Eruptions bring high-temperature magma or gas to the surface; thermal observations of these eruptions can be used to determine the timeline of eruptive sequences or eruptive processes. In 2014, a new-generation meteorological satellite, Himawari-8, which carried a new sensor, the Advanced Himawari Imager (AHI), was launched. The AHI makes high-frequency infrared observations at a spatial resolution of 2 km during 10-min observation cycles. We analyzed an effusive eruption that occurred in 2015 at Mt Raung in Indonesia using these AHI images, which was the first attempt applying them to volcanological study. Based on the detailed analysis of the time-series variations in its thermal anomalies, this eruptive sequence was segmented into a Precursory Stage, Pulse 1, Pulse 2 and a Terminal Stage. Pulses 1 and 2 are effusive stages that exhibited a consecutive two-pulse pattern in their variations, reflecting changes in the lava effusion rate; the other stages are non-effusive. We were also able to determine the exact times of the onset and reactivation of lava flow effusion, as well as the precursory signals that preceded these events.

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Section: Long-term Variations In Thermal Data and Stage Segmentation supporting

confidence: 71%

Himawari-8 infrared observations of the June–August 2015 Mt Raung eruption, Indonesia

Kaneko

Takasaki

Maeno

et al. 2018

Earth Planets Space

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show abstract

“…Automatic RSAM calculation (Endo and Murray, 1991) is in place, and some algorithms based on time-frequency domain analysis to both auto-detect and classify volcanic seismic events are being tested. More detailed analyses, including volcanic event classification, source location and spectral analysis, are performed with the SEISAN package (Ottemöller et al, 2012) and Matlab.…”

Section: The Networkmentioning

confidence: 99%

Investigating volcanic hazard in Cape Verde Islands through geophysical monitoring: network description and first results

Faria¹,

Fonseca²

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. We describe a new geophysical network deployed in the Cape Verde Archipelago for the assessment and monitoring of volcanic hazards as well as the first results from the network. Across the archipelago, the ages of volcanic activity range from ca. 20 Ma to present. In general, older islands are in the east and younger ones are in the west, but there is no clear age progression of eruptive activity as widely separated islands have erupted contemporaneously on geological timescales. The overall magmatic rate is low, and there are indications that eruptive activity is episodic, with intervals between episodes of intense activity ranging from 1 to 4 Ma. Although only Fogo Island has experienced eruptions (mainly effusive) in the historic period (last 550 yr), Brava and Santo Antão have experienced numerous geologically recent eruptions, including violent explosive eruptions, and show felt seismic activity and geothermal activity. Evidence for recent volcanism in the other islands is more limited and the emphasis has therefore been on monitoring of the three critical islands of Fogo, Brava and Santo Antão, where volcanic hazard levels are highest. Geophysical monitoring of all three islands is now in operation. The first results show that on Fogo, the seismic activity is dominated by hydrothermal events and volcano-tectonic events that may be related to settling of the edifice after the 1995 eruption; in Brava by volcano-tectonic events (mostly offshore), and in Santo Antão by volcano-tectonic events, medium-frequency events and harmonic tremor. Both in Brava and in Santo Antão, the recorded seismicity indicates that relatively shallow magmatic systems are present and causing deformation of the edifices that may include episodes of dike intrusion.

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“…Variations in continuous recordings of seismic amplitudes (e.g., RSAM measurements) have been widely used to monitor the eruptive activity of volcanoes (e.g., Endo and Murray, 1991;Cornelius and Voight, 1994). These measurements however concern both signal and noise amplitudes.…”

Section: Steady Increase Of the Base Level Of The Noise Spectrum At Hmentioning

confidence: 99%

Pre-failure behaviour of an unstable limestone cliff from displacement and seismic data

Got

Mourot

Grangeon

2010

Nat. Hazards Earth Syst. Sci.

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Abstract. We monitored the displacement and seismic activity of an unstable vertical rock slice in a natural limestone cliff of the southeast Vercors massif, southeast France, during the months preceding its collapse. Displacement measurements showed an average acceleration of the movement of its top, with clear increases in the displacement velocity and in the discrete seismic event production rate during periods where temperature falls, with more activity when rainfall or frost occurs. Crises of discrete seismic events produce high amplitudes in periodograms, but do not change the high frequency base noise level rate. We infer that these crises express the critical crack growth induced by water weakening (from water vapor condensation or rain) of the rock strength rather than to a rapid change in applied stresses. Seismic noise analysis showed a steady increase in the high frequency base noise level and the emergence of spectral modes in the signal recorded by the sensor installed on the unstable rock slice during the weeks preceding the collapse. High frequency seismic noise base level seems to represent subcritical crack growth. It is a smooth and robust parameter whose variations are related to generalized changes in the rupture process. Drop of the seismic noise amplitude was concomitant with the emergence of spectral modes -that are compatible with high-order eigenmodes of the unstable rock sliceduring the later stages of its instability. Seismic noise analysis, especially high frequency base noise level analysis may complement that of inverse displacement velocity in earlywarning approaches when strong displacement fluctuations occur.

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Real-time Seismic Amplitude Measurement (RSAM): a volcano monitoring and prediction tool

Cited by 279 publications

References 12 publications

Himawari-8 infrared observations of the June–August 2015 Mt Raung eruption, Indonesia

Himawari-8 infrared observations of the June–August 2015 Mt Raung eruption, Indonesia

Investigating volcanic hazard in Cape Verde Islands through geophysical monitoring: network description and first results

Pre-failure behaviour of an unstable limestone cliff from displacement and seismic data

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