- Full paper
- Open Access
Active monitoring at an active volcano: amplitude-distance dependence of ACROSS at Sakurajima Volcano, Japan
© Yamaoka et al.; licensee Springer. 2014
Received: 3 October 2013
Accepted: 22 April 2014
Published: 7 May 2014
First testing of volcanic activity monitoring with a system of continuously operatable seismic sources, named ACROSS, was started at Sakurajima Volcano, Japan. Two vibrators were deployed on the northwestern flank of the volcano, with a distance of 3.6 km from the main crater. We successfully completed the testing of continuous operation from 12 June to 18 September 2012, with a single frequency at 10.01 Hz and frequency modulation from 10 to 15 Hz. The signal was detected even at a station that is 28 km from the source, establishing the amplitude decay relation as a function of distance in the region in and around Sakurajima Volcano. We compare the observed amplitude decay with the prediction that was made before the deployment as a feasible study. In the prediction, we used the existing datasets by an explosion experiment in Sakurajima and the distance-dependent amplitude decay model that was established for the ACROSS source in the Tokai region. The predicted amplitude in Sakurajima is systematically smaller than that actually observed, but the dependence on distance is consistent with the observation. On the basis of the comparison of the noise level in Sakurajima Volcano, only 1-day stacking of data is necessary to reduce the noise to the level that is comparable to the signal level at the stations in the island.
Many observation methods are used in monitoring volcanic activity to estimate the migration of magma associated with volcanic eruptions. Crustal deformation is widely used in volcano monitoring to obtain information on the pressure source beneath volcanoes. Leveling surveys in and around volcanoes have long been used to detect the location and the pressure change of magma chambers since the pioneering work of Omori (1916) and a model calculation by Mogi (1957). Data of leveling surveys are also used for detecting the intrusion of dykes (e.g., Hashimoto and Tada1990). Quantitative modeling of dykes has been widely used using the comprehensive formulation by Okada (1985). Since the innovative success of Global Positioning System (GPS), geodetic networks have been established in many volcanoes, and their crustal deformations are monitored in near-real time. The crustal deformations are usually interpreted as inflation or deflation of magma reservoirs or dyke intrusions.
Seismic activities have also long been used to monitor volcanic activities. Activation or deactivation of earthquakes, changes in hypocenter distribution, and types of earthquakes are widely used as empirical tools to warn volcanic eruptions. McNutt (1996) proposed a generic swarm model of volcanic earthquakes to evaluate the temporal sequence of volcanic activity. Intrusions of dykes are usually inferred from hypocenter migrations (e.g., Sakai et al.2001 for the Miyakejima Volcano). Long-period (LP) events or volcanic tremors are used to infer magma or hydrothermal activity in volcanoes. Very long period (VLP) events, especially, are used to model the vibration of magma plumbing systems (e.g., Kumagai2006).
Electromagnetic observations are generally used for monitoring thermal activity of volcanoes. Heating or cooling of rocks in volcanoes can be detected with the increase or decrease of magnetic fields near volcanoes. Emplacement of magma or changes in hydrothermal activity affect the resistivity structure beneath volcanoes, which can be monitored by electromagnetic surveys. For example, pre-eruptive activity of the caldera formation at Miyakejima Volcano in 2000 was monitored with magnetic and electric field variations (Sasai et al.2002).
Temporal changes in the propagation properties of seismic wave are a relatively new tool for monitoring volcanic activities. S-wave splitting has been regarded as a stress measure (Crampin1994) and used for monitoring volcanic activity (e.g., Gerst and Savage2004). Seismic interferometry using passive sources, such as ambient noise, has recently been applied to detect the temporal variation of seismic propagation in volcanic regions to monitor their activity. Grêt and Roel (2005) monitored temporal changes of the seismic structure in Mt. Erebus with coda wave interferometry from December 1999 to February 2000, suggesting that the change of cross correlation between two different seismic events might indicate changes in the uppermost lava lake. Seismic interferometry has been applied to other volcanoes, such as Merapi (Sens-Schoenfelder and Wegler2006) and Reunion Volcanoes (Brenguier et al.2008), to monitor the temporal changes in volcanic activity.
Active sources are also used to detect temporal variations of seismic propagation properties in volcanoes, though few trials have been made. Active sources have an advantage over natural sources in that source parameters such as time and location are well constrained. Nishimura et al. (2005) examined a temporal change in seismic velocity by repeating six explosion sources in a 6-year period near Iwate Volcano throughout its active period. Tsutsui et al. (2011) conducted repeating reflection seismic surveys in Sakurajima Volcano to investigate the temporal changes in reflection image.
Traditional artificial sources were used for monitoring seismic propagation properties using repeating operations with regular time intervals. Explosive or impact sources, which have been frequently used, can destroy the ambient rocks and could change the propagation property around the source. To overcome such shortcomings, a controlled source for long-term continuous monitoring, named ACROSS, which stands for Accurately Controlled Routinely Operated Signal System, was developed (Kumazawa and Takei1994). In the ACROSS, the seismic signal is generated by the centrifugal force of a rotating eccentric mass. The rotation is highly stabilized to maximize the stacking performance in order to increase the signal-to-noise ratio. The transfer functions between the source and receivers are calculated with a convolution of received signals with the source signal.
ACROSS was first deployed in 1996 at two test sites, Awaji Island and Tono region in Japan, to evaluate its performance. The rotation is accurately controlled by an AC servo motor with a feedback inverter, and the rotational angle is synchronized to the pulse sequences given by a GPS clock. As most of the seismic stations are operated with reference to a GPS clock, we can establish a remote synchronization between the ACROSS source and seismic stations (Yamaoka et al.2001). Fifteen months of monitoring at Awaji site started in January 2000, and it succeeded in detecting a temporal change associated with strong ground motion by nearby earthquakes (Ikuta and Yamaoka2004), which shows a sudden delay and gradual recovery of seismic velocity, presumably due to ground water movement.
Deployment of ACROSS in Sakurajima
Sakurajima Volcano, Japan, is one of the most active volcanoes in the world and is located in the southern part of Kyushu Island, Japan. Sakurajima Volcano is a small island and is located at the rim of the Aira Caldera that produced a gigantic silicic eruption about 25,000 years ago (Aramaki1969). Sakurajima Volcano experienced flank and summit eruptions in historic times (Kobayashi and Tameike2002). Violent eruptions with effusion of andesitic lava took place in 1476, 1779, 1914, and 1946. The volume of lava in the 1914 eruption was about 1.5 km3 (Ishihara et al.1981), and the flow covered the channel between the Sakurajima and Kyushu Islands. The results of instrumental observations for recent eruptive activities are summarized by the Japan Meteorological Agency (2013). The current eruptive activity started in 1955 and remained at a high level from 1974 to 1992. After this period, Sakurajima was less active until 2006. The eruption activity started anew in June 2006 from the Showa Crater located about 500 m east of the Minamidake Crater, which has been active and exploded tens of thousands of times since 1974. The number of explosions at the Showa Crater amounts to more than a thousand in 2010. Studies on crustal movement revealed two main magma sources in and around Sakurajima Volcano (Ishihara1990), showing a large magma source beneath the Aira Caldera located at a depth of about 10 km below sea level, and a small magma source located about 4 km beneath the summit of Sakurajima Volcano. Hidayati et al. (2007) estimated the location of magma sources by analyzing volcano tectonic earthquakes. They showed that a magma source exists at a depth of 5 km and small magma pockets are distributed vertically from the depths of 2 to 4 km below the summit.
Deployment of ACROSS
A PC-based controller that can make precise operations on the motor is the essential part of ACROSS (Kunitomo and Kumazawa2004). It consists of a GPS clock (XL-DC, TrueTime Inc., Santa Rosa, CA, USA), pulse generators (ACROSS-SG2, Digital Signal Technology Inc., Asaka, Japan), and control software (ROSET-TA2012) on a Windows PC. The pulse generator provides a series of pulses to the power control gear, which drives the AC servo motor so that the rotation angle is proportional to the number of pulses given to it. The timing of pulses produced by the pulse generator is precisely synchronized to the GPS clock. Therefore, this pulse generator can drive the vibrator so that it produces a sinusoidal force with frequency modulation (FM) by expanding and shrinking the intervals of pulses. In ACROSS, the FM operation is a fundamental technique to produce plural sinusoids simultaneously with one vibrator.
The control software has multiple functions. It monitors the states of the mass rotation, such as the rotational velocity, mass position, and motor torque. The notable function of the software is to switch the rotation direction automatically at regular time intervals. The switching interval is usually chosen to be either 1 or 2 h. We can synthesize a linear vibration in any direction with a combination of clockwise and anticlockwise rotations. This means that we can monitor the temporal variation of seismic propagation properties for multiple excitation directions. As the vibrator rotates around the vertical axis, radial and transverse vibrations with reference to the station direction are synthesized to obtain the transfer function related to P and S waves, respectively, which is a great advantage of the system.
The source site has Internet connection for remote monitoring and remote control of ACROSS. This dramatically reduces the frequency of maintenance visits. In the summer time, electric power outages and vibrator stoppages occur frequently due to unstable weather conditions, including heavy rain and typhoons with lightning. The vibrators can be restarted via the Internet connection using a VNC protocol, which enables us to stop or restart the vibrator remotely, without visiting the site. The rotation frequency and phase, the motor torque, and oil temperature are monitored and recorded by the PC to infer the cause of any troubles, shortening the time before repairs. A web camera with a microphone is also deployed at the vibrators' location so that the lubricant circulators, the control gear, and PC-based controllers are visible, making it easy to perform a visual inspection of the system.
First signal test
The first test operation began on 12 June 2012 and continued until 17 September 2012, for 97 days. During this test period, one vibrator was operated with a single frequency at 10.01 Hz, and the other was operated with FM from 10 to 15 Hz and a modulation period of 50 s. We chose 10.01 Hz for the single frequency so as not to overlap with the frequency components produced by the other vibrator in FM operation. The FM operation produces a series of sinusoids from 10.00 to 15.00 Hz with a 0.02-Hz interval. The rotation direction was switched every 2 h to synthesize two independent linear excitation forces. The received signals of two sequential operations, one of which is clockwise and the other is anticlockwise rotation of the source, are linearly combined with an appropriate phase shift. This operation synthesizes the signals at the seismic stations by radial and transverse linear excitations. The rate of operation in the first test period was 88%. The main cause of the suspension was power instability or failure due to lightning or storm around the site. In most cases, the system was restarted remotely.
The unit of spectral amplitude is adjusted to meters per second (m/s), which represents the amplitude of a single sinusoidal wave. Note that the amplitude unit in this spectrum plot is not (m/s)/Hz1/2 which is generally used in conventional spectrum plots. We adopt the unit m/s, because the signal emitted from ACROSS is composed of a finite number of sinusoids with constant amplitudes. In this unit, the amplitude of ACROSS signals in the frequency domain stays constant, independent of the stacking length. If we adopt (m/s)/Hz1/2, the spectral peaks of the ACROSS signal increase with the length of the stacking period, while the noise level stays constant. We prefer m/s for the amplitude unit to make the ACROSS signal invariable while noise levels decrease proportionally to the square root of the stacking time period.
The signal from the source that is operated in a single frequency (10.01 Hz) is clearly seen even at the stations off Sakurajima Island. The station KORH (Figure 3a), which is located 19.5 km from the source site, shows a clear spectral peak at 10.01 Hz, with a signal-to-noise ratio (SNR) of about 100 in all the components, with a stacking length of 88 days. The signal of the source in FM operation is also seen in the spectrum from 10 to 15 Hz. The station KURN (Figure 3b), which is located 7.5 km from the source site on the other side of the summit, shows clear spectral peaks. The SNRs are larger than those at KORH, even though the stacking period is 71 days. The signal at HAR (Figure 3c), which is located 1.1 km from the source site, has a very good SNR not only because of the distance, but also because of the low-noise environment in the deep borehole. The SNR for a single sinusoid at 10.01 Hz is about 1,000 for most of the components, and the SNR for the FM signal is about 100. Other spectral peaks, which are typically seen at KORH, are caused by the data telemetry system at the station. Small noise that is synchronized to the GPS clock is generated in the data telemetry system, resulting in spectral peaks with multiples of exactly 1.0 Hz.
Comparison to Toyohashi site
The same models of ACROSS vibrators were already in operation at the Toyohashi site in the Tokai region, Japan, when ACROSS was deployed in Sakurajima. We have been operating the ACROSS at Toyohashi site to monitor the temporal change of seismic propagation property associated with the subduction process of the Philippine Sea plate. In addition, we deployed an ACROSS at Sakurajima Volcano for monitoring its activities. Before the deployment, we investigated the detectability of signal from the ACROSS source that was to be deployed in Sakurajima using the observation data in the Tokai region with ACROSS at Toyohashi. In this section, we show the results of the investigation comparing them with the actual observational result. To assess the feasibility of signal detection at Sakurajima, we used the amplitude decay relation as a function of distance obtained in the monitoring experiment of ACROSS in the Tokai region and an explosion experiment in Sakurajima. The process shown here is useful to assess the feasibility of using ACROSS at any other locations.
Explosion experiment at Sakurajima
An explosion experiment for which we analyzed the amplitude decay as a function of distance was carried out in 2008 in and around Sakurajima Island (Iguchi et al.2009). We compared the amplitude decays between the explosion source and the ACROSS source in the Tokai region.
From the experiment dataset, we used the record of shot 2 (S02 in Figure 6) for the estimation of amplitude decay with distance. Shot 2 was located close to the ACROSS source site and is suitable for comparison. Although there were several other shots that were closer to the ACROSS site than shot 2, we do not use them because their dynamite weight was only 20 kg, while the dynamite for shot 2 weighed as much as 200 kg.
where x is distance from the source and a is the intercept term that is regarded as the source intensity. The term 1/x indicates the amplitude decay by geometrical spreading for the body wave, and exp (-bx) indicates attenuation within the medium. This equation is the same as that used in the location of hypocenters of volcanic earthquakes by Battaglia and Aki (2003). As there are no marked later phases that correspond to surface waves (Figure 7), we used the geometrical spreading factor for body waves. The b is connected with quality factor Q with Equation 2, where β denotes wave velocity.
In this calculation, we used the horizontal distances between the source and the receivers. Let us examine the decay change when the distance along the ray for more realistic velocity structure is used. To examine the difference, we try to use the one-dimensional velocity structure that follows a simple linear function. We assume a velocity gradient of 0.5 km s-1 m-1 and surface velocity of 3.5 km s-1, which provides a maximum depth of 5.2 km for the ray traveling 25 km from the source. The corresponding b values for the ray-based distance are 0.16, 0.19, 0.11, and 0.13, respectively. These values provide Q p of 80, 100, 120, and 150, respectively. The differences between the two estimations of Q are about 50%, which is the uncertainty owing to the model difference of the velocity structure.
It is interesting to compare these Q p values with those obtained in other methods or other volcanoes. Iguchi (1994) estimated the Q p value of Sakurajima Volcano using the spatial decay of amplitude of volcanic earthquakes and obtained the Q p value of about 20. He used A-type earthquakes, in which short-period component of around 10 Hz predominates, with straight-line approximation of ray path between the epicenters and seismic stations in the island. As he assumed body wave for geometrical spreading factor, his Q p value can be directly compared with our result, which is about 50. His result is smaller than ours, which may result from the hypocenter locations of A-type earthquakes, being just beneath the summit crater with depths of 1 to 4 km. Low Q p value may indicate the high attenuation nature in the region beneath the summit crater. Hirata and Uchiyama (1981) estimated the attenuation in the Aira Caldera region, which neighbors Sakurajima Volcano, with spatial amplitude decay ratio, showing a Q p of about 80. This supports our inference that the region of low Q value estimated by Iguchi (1994) is localized near the vent.
Q values are estimated for other volcanoes. Sudo (1991) estimated the attenuation beneath Aso Volcano, Japan, concluding that the Q p is about 100. Bianco et al. (1999) estimated the Q p at Mt. Vesuvius, Italy, to be about 35 with the frequency decay method. Patane et al. (1994) estimated the attenuation using the records of seismic stations around Mt. Etna, showing that the Q p varies between 50 and 110 among the stations in the frequency range of 2 to 15 Hz. Giampiccolo et al. (2007) estimated the attenuation at Mt. Etna to fit the power law Q = Q 0 f n with the spectral ratio method. They found that Q p for the upper 5 km of the crust was estimated to be 16f0.8 with some ambiguity, that is about 100 at 10 Hz. Martinez-Arevalo et al. (2005) built the 3-D attenuation tomography in the shallow part (-2 to 2 km depth) at Mt. Etna and showed the large heterogeneity in Q p , ranging between 10 and 250, in the frequency range of 2 to 30 Hz. They also found a region of low Q p between 10 and 30 at the place of presumed dike intrusion in 2001. The Q p we obtained for Sakurajima Volcano is comparable to the Q p values in other volcanoes.
Amplitude decay in Tokai
We predict the amplitude decay relations as a function of distance for the ACROSS source at Sakurajima from that in Tokai. We assume that both relations for Sakurajima and the Tokai region share the same source intensity a in Equation 1, but that each has its own b that is characteristic of each region. The red curve in Figure 10 indicates the predicted amplitude decay with distance for the ACROSS source in Sakurajima Volcano. In this curve, we use b = 0.30 that is obtained for the stations on Sakurajima Island. Both lines run very close to each other below 1 km, and the curve for Sakurajima decays more rapidly and becomes one tenth of the curve for Tokai region at 10 km.
We compare the amplitude decay curve that is predicted for Sakurajima with the actual data we obtained in the first operation test. As the decay curve in Figure 10 is obtained from the FM operation from 10 to 20 Hz at the Toyohashi site, and the data in the first operation test in Sakurajima are obtained by the FM operation from 10 to 15 Hz and a single frequency of 10.01 Hz, we need to convert their amplitudes to be able to compare them with each other. Therefore, we convert the amplitude decay curve that is predicted for FM operation of 10 to 20 Hz into the decay curve for FM operation of 10 to 15 Hz. We also convert the amplitude of the single frequency of 10.01 Hz to the mean spectral amplitude of FM operation of 10 to 15 Hz.
In the conversion, we make two assumptions. One is that the energy of the ACROSS signal is the sum of the square of the peaks in the amplitude spectrum. The other is that the attenuation is the same for the frequency range in this study. Based on these assumptions, we make the conversion as described below.
Next, we convert the amplitude of the spectral peak of single frequency operation at 10.01 Hz into the corresponding mean amplitude of FM operation of 10 to 15 Hz. We calculate the energy ratio between single frequency operation at 10.01 Hz and FM operation of 10 to 15 Hz. The energy ratio is calculated by integrating the square of the force by FM operation (Equation 3) and single frequency over the same period T. The calculated energy ratio of the FM operation over the single frequency is 2.627. Assuming the energy is equally distributed into 251 peaks between 10 and 15 Hz, the calculated mean amplitude is 0.102 times that of the single frequency of 10.01 Hz.
The converted amplitudes are plotted in Figure 11. In the figure, we plot the results of two types of amplitude averaging. One is the averaging over the receiver components (left panel), and the other is the averaging over the source excitations (right panel). As explained in the ‘First signal test’ section, the transfer function for each station has six components, which is the combination of two components for the source excitations and three components for the receiver. The panel on the left shows the mean amplitude of three components at receivers for transverse and radial excitations of the source. The mean amplitudes for the single sinusoid operation at 10.01 Hz are labeled 10.01 t and 10.01 r for transverse and radial excitations, respectively. Those of the FM operations are labeled FM t and FM r. There is no systematic difference in the mean amplitude between transverse and radial excitations. The panel on the right shows the amplitudes of transverse and radial components of the horizontal motions at receivers averaged over two excitation components of the source. There is no systematic difference in the receiver components.
In Figure 11, two decay curves are drawn. Red curves are the same as that in Figure 10, which use the b value for the attenuation on Sakurajima Island. The black curves show the decay corresponding to the b value for the attenuation on and around Sakurajima Island. The decay trend of observation amplitude is similar to what we have predicted in the above method, but most of the amplitudes are above the prediction curve.
Apparently, the reason for the discrepancy is the underestimation of the source intensity a. A possible reason for the underestimate is the difference in the deployment condition between Sakurajima and Toyohashi, i.e., stiffness of the ground to which the vibrator is fixed. The ACROSS vibrators at the Sakurajima site are deployed in a pyroclastic deposit, whereas those at the Toyohashi site are in a clay layer. The conversion efficiency from force to energy that is transmitted to the far field may depend on the stiffness of the ground where the vibrator is deployed. The simple analogy of strain energy in a compressed or stretched spring suggests that more strain energy is stored in a medium with less stiffness. Therefore, it is natural to infer that the vibrator transfers more far-field energy from the source that is deployed in the ground with less stiffness. In other words, the ground coupling is better at the Sakurajima site than at the Toyohashi site, which results in larger source intensity a for Sakurajima even if the same vibrator is used. The ground coupling is the issue of dynamic interaction of vibrators and the surrounding ground, which is to be solved in future work. Mass of the vibrators and elastic nature of the ground may affect the coupling efficiency.
Another possible reason for the underestimate of source intensity a could be the use of epicenter distances rather than the distances along ray paths. We try to evaluate the effect of the use of ray path-based distance on the source intensity with one-dimensional simple velocity structure model for Tokai area as in the section ‘Explosion experiment at Sakurajima’. We assume a velocity gradient of 0.13 km s-1 m-1 and surface velocity of 4.5 km s-1, which gives a maximum depth of 7.4 km for the ray traveling 48 km of epicenter distance. The source intensity that is estimated by using the distance along ray paths is just 10% more than that by epicenter distances. Therefore, the use of epicenter distance is not the main cause of the underestimate.
Surface deployment of a seismometer may record a signal with large amplitude. The two stations between 2.0 and 3.0 km in Figure 11 are deployed on the surface (Tameguri et al.2011), showing a larger amplitude compared with other stations, which are deployed in boreholes.
Once the amplitude decay curve is obtained, the SNR is predicted using the level of ground noise at the seismic stations. Resolution of temporal variation of the ACROSS signal depends on the SNR after the data stacking (Ikuta et al.2002). We have estimated the noise level in and around Sakurajima Volcano using the same seismic data of the explosion experiment as used in the previous section. We picked up 10-s-long records before the onset of the P wave in the data at each station to estimate the noise level. We calculated the RMS of the amplitude spectrum of the noise in the frequency bands between 10 and 20 Hz. This value is recognized as the noise level in the corresponding frequency range. We carried out this calculation on the data from each station for all the 15 shot sources. We adopted the third lowest value of 15 data as the representative noise level at each station. This operation avoids the traffic noise that occasionally disturbs the signal, as well as the artificially small noise level that might be due to the missed selection of amplitude gain.
The spectral plot for station KURN, for example, is created with the stacked data of 71 days. The noise level for 71 days is reduced by 783 times smaller than that for 10-s data. Therefore, the mean noise on Sakurajima Island is reduced to 2.5 × 10-12 m/s after stacking, which is comparable to the noise level at KURN between 10 and 20 Hz. The noise level at HAR, which is also on Sakurajima, is almost the same level. This means that the noise estimation in this study is valid.
We shall compare the noise level with the amplitude decay relation as shown in Figure 11. The noise level for the 10-s data is 2.0 × 10-9 m/s, which is comparable to the predicted amplitude decay curves at 1.0-km distance. The noise level after stacking of 1 day is reduced to 2.1 × 10-11 m/s, which is comparable to the level of predicted curves at 10 km, and is several times smaller than the actual observation.
Seismic sources, named ACROSS, are deployed at Sakurajima Volcano for the first time in volcanic area in March of 2012. Two sources are deployed at the northwestern flank of Sakurajima Volcano with a distance of 3.6 km from the main crater. Signals received by the seismic stations are investigated for the test operation from 12 June to 18 September 2012, in which sources are operated with a single frequency at 10.01 Hz and with frequency modulation of 10 to 15 Hz. The signal of the ACROSS source is detectable even at the station off Sakurajima Island. The amplitudes and the decay relation with source distance are compared with the amplitude decay model established in the Tokai region for the ACROSS source. The amplitude decay relation with distance in Sakurajima using the ACROSS sources is predicted from the amplitude data of an explosion experiment, assuming the same source intensity as that of the ACROSS source in the Tokai region. The predicted amplitude is systematically smaller than that actually observed, but the dependence with distance is consistent with the observation, probably because of the difference in the ground stiffness at the source site. The noise level in Sakurajima that is estimated using the data of explosion experiment is consistent with the noise in the stacking data of the ACROSS signal.
We are very grateful to the Sakurajima Volcano seismic exploration group for providing observation data for our analysis. We used the continuous data from seismic stations that are operated by National Research Institute for Earth Science and Disaster Prevention, Kyoto University, Kagoshima University, and Nagoya University. The study was supported by JSPS KAKENHI Grant-in-Aid for Scientific Research (B) 23340130.
- Aramaki S: Geology and pyroclastic flow deposits of the Kokubu area, Kagoshima prefecture. J Geolog Soc Japan 1969, 75: 425–442. 10.5575/geosoc.75.425View ArticleGoogle Scholar
- Battaglia J, Aki K: Location of seismic events and eruptive fissures on the Piton de la Fournaise volcano using seismic amplitudes. J Geophys Res 2003. doi:10.1029/2002JB002193Google Scholar
- Bianco F, Castellano E, Del Pezzo E, Ibanez JM: Attenuation of short-period seismic waves at Mt Vesuvius, Italy. Geophys J Int 1999, 138: 67–76. 10.1046/j.1365-246x.1999.00868.xView ArticleGoogle Scholar
- Brenguier F, Sapiro NM, Campillo M, Ferrazzini V, Duputel Z, Coutant O, Nercessian A: Towards forecasting volcanic eruptions using seismic noise. Nat Geosci 2008, 1: 126–130. 10.1038/ngeo104View ArticleGoogle Scholar
- Crampin S: The fracture criticality of crustal rocks. Geophys J Int 1994, 118: 428–438. 10.1111/j.1365-246X.1994.tb03974.xView ArticleGoogle Scholar
- Gerst A, Savage MK: Seismic anisotropy beneath Ruapehu volcano: a possible eruption forecasting tool. Science 2004, 306: 1543–1547. doi:10.1126/science.113445View ArticleGoogle Scholar
- Giampiccolo E, D'Amico S, Patane D, Gresta S: Attenuation and source parameters of shallow microearthquakes at Mt. Etna volcano, Italy. Bull Seismol Soc Am 2007, 97: 184–197. doi:10.1785/0120050252View ArticleGoogle Scholar
- Grêt A, Roel S: Monitoring rapid temporal change in a volcano with coda wave interferometry. Geophys Res Lett 2005. doi:10.1029/2004GL021143Google Scholar
- Hashimoto M, Tada T: Crustal deformations associated with the 1986 fissure eruption of Izu-Oshima volcano, Japan, and their tectonic significance. Phys Earth Planet Int 1990, 60: 324–338. 10.1016/0031-9201(90)90272-YView ArticleGoogle Scholar
- Hidayati S, Ishihara K, Iguchi M: Volcano-tectonic earthquakes during the stage of magma accumulation at the Aira caldera, southern Kyushu, Japan. Bull Volcanol Soc Japan 2007, 52: 1289–1309.Google Scholar
- Hirata T, Uchiyama T: Damping area in the Aira caldera of south Kyushu. Bull Seismol Soc Japan 1981, 34: 435–437.Google Scholar
- Iguchi M: A vertical expansion source model for the mechanisms of earthquakes originated in the magma conduit of an andesitic volcano: Sakurajima, Japan. Bull Volcanol Soc Japan 1994, 39: 49–67.Google Scholar
- Iguchi M, Tameguri T, Yamamoto K, Osima H, Maekawa T, Mori H, Suzuki A, Tsutui T, Imai M, Tsushima K, Yagi N, Ueki S, Nakayama T, Yamamoto Y, Takagi R, Ii S, Koga S, Nishimura T, Anggono T, Yamamoto M, Oikawa J, Osada N, Ichihara M, Tsuji H, Aoki Y, Morita Y, Watanabe A, Nogami K, Yamawaki T, Watanabe T, et al.: The 2008 project of artificial explosion experiment at Sakurajima volcano. Ann Disaster Prev Res Inst, Kyoto Univ 2009, 52: 293–307.Google Scholar
- Ikuta R, Yamaoka K, Miyakawa K, Kunitomo T, Kumazawa M: Continuous monitoring of propagation velocity of seismic wave using ACROSS. Geophys Res Lett 2002. doi:10.1029/2001GL013974Google Scholar
- Ikuta R, Yamaoka K: Temporal variation in the shear wave anisotropy detected using the Accurately Controlled Routinely Operated Signal System (ACROSS). J Geophys Res 2004. doi:10.1029/2003JB002901Google Scholar
- Ishihara K, Takayama T, Tanaka Y, Hirabayashi J: Lava flows at Sakurajima Volcano (I) – volume of the historical lava flows. Ann Disaster Prev Res Inst, Kyoto Univ 1981, 24: 1–10.Google Scholar
- Ishihara K: Pressure sources and induced ground deformation associated with explosive eruptions at an andesitic volcano: Sakurajima volcano, Japan. In Magma transport and storage. Edited by: Ryan M. Chichester: John Wiley and Sons; 1990.Google Scholar
- Japan Meteorological Agency: National catalogue of the active volcanoes in Japan. 4th edition. Tokyo: Japan Meteorological Agency; 2013.Google Scholar
- Kobayashi T, Tameike T: History of eruptions and volcanic damage from Sakurajima volcano, southern Kyushu, Japan. Quaternary Res 2002, 41: 269–278. 10.4116/jaqua.41.269View ArticleGoogle Scholar
- Kumagai H: Temporal evolution of a magmatic dike system inferred from the complex frequencies of very long period seismic signals. J Geophys Res 2006. doi:10.1029/2005JB003881Google Scholar
- Kumazawa M, Takei Y: Active method of monitoring underground structures by means of accurately controlled rotary seismic source (ACROSS) 1. Purpose and principle. Abstracts of fall meeting of the Seismological Society of Japan 1994, 158.Google Scholar
- Kunitomo T, Kumazawa M: Active monitoring of the Earth's structure by the seismic ACROSS - transmitting and receiving technologies of the seismic ACROSS. Proceedings of the 1st International Workshop on Active Monitoring in the Solid Earth Geophysics, Mizunami 2004.Google Scholar
- Martinez-Arevalo C, Patane D, Rietbrock A, Ibanez JM: The intrusive process leading to the Mt. Etna 2001 flank eruption: constraints from 3-D attenuation tomography. Geophys Res Lett 2005, 32: L21309.View ArticleGoogle Scholar
- McNutt SR: Seismic monitoring and eruption forecasting of volcanoes: a review of the state-of-the-art and case histories. In Monitoring and mitigation of volcano hazards. Edited by: Scarpa R, Tilling R. New York: Springer; 1996:99–146.View ArticleGoogle Scholar
- Miyamachi H, Tomari C, Yakiwara H, Iguchi M, Tameguri T, Yamamoto K, Ohkura T, Ando T, Onishi K, Shimizu H, Yamashita Y, Nakamichi H, Yamawaki T, Oikawa J, Ueki S, Tsutsui T, Mori H, Nishida M, Hiramatsu H, Koeda T, Masuda Y, Katou K, Hatakeyama K, Kobayashi T: Shallow velocity structure beneath the Aira caldera and Sakurajima volcano as inferred from refraction analysis of the seismic experiment in 2008. Bull Volcanol Soc Japan 2013, 58: 227–237.Google Scholar
- Mogi K: On the relation between the eruptions of Sakurajima Volcano and the crustal movements in its neighborhood. Bull Volcanol Soc Japan 1957, 1: 9–18.Google Scholar
- Nishimura T, Tanaka S, Yamawaki T, Yamamoto H, Sano T, Sato M, Nakahara H, Uchida N, Hori S, Sato H: Temporal changes in seismic velocity of the crust around Iwate volcano, Japan, as inferred from analyses of repeated active seismic experiment data from 1998 to 2003. Earth Planets Space 2005, 57: 491–505.View ArticleGoogle Scholar
- Okada Y: Surface deformation due to shear and tensile faults in a half-space. Bull Seismol Soc Am 1985, 75: 1135–1154.Google Scholar
- Omori F: The Sakura-Jima eruptions and earthquakes II. Bull Imperial Earthquake Investigation Committee 1916, 8: 35–179.Google Scholar
- Patane D, Ferrucci F, Cresta S: Spectral features of microearthquakes in volcanic areas: attenuation in the crust and amplitude response of site at Mt. Etna, Italy. Bull Seismol Soc Am 1994, 84: 1842–1860.Google Scholar
- Sakai S, Yamada T, Ide S, Mochizuki M, Shiobara H, Urabe T, Hirata N, Shinohara M, Kanazawa T, Nishizawa A, Fujie G, Mikada H: Magma migration from the point of view of seismic activity in the volcanism of Miyake-jima island in 2000. J Geography 2001, 110: 145–155. 10.5026/jgeography.110.2_145View ArticleGoogle Scholar
- Sasai Y, Uyeshima M, Zlotnicki J, Utada H, Kagiyama T, Hashimoto T, Takahashi Y: Magnetic and electric field observation during the 2000 activity of Miyake-jima volcano, Central Japan. Earth Planet Sci Lett 2002, 203: 769–777. 10.1016/S0012-821X(02)00857-9View ArticleGoogle Scholar
- Sens-Schoenfelder C, Wegler U: Passive image interferometry and seasonal variations of seismic velocities at Merapi Volcano. Indonesia Geophys Res Lett 2006. doi:10.1029/2006GL027797Google Scholar
- Sudo Y: An attenuating structure beneath the Aso Caldera determined from the propagation of seismic waves. Bull Volcanol 1991, 53: 99–111.View ArticleGoogle Scholar
- Tameguri T, Iguchi M, Sonoda T, Ichikawa N: Hypocenter distributions of volcanic earthquakes at Sakurajima Volcano (2011–2012). In Annual report of research on Sakurajima volcano with comprehensive observation. Edited by: Iguchi M. Uji, Japan: Disaster Prevention Research Institute of Kyoto University; 2011:2–6.Google Scholar
- Tsutsui T, Tameguri T, Iguchi M, Oikawa J, Oshima H, Maekawa T, Aoyama H, Ueki S, Hirahara S, Nogami K, Ohminato T, Ichihara M, Tsuji H, Horikawa S, Okuda T, Shimizu H, Matsushima T, Ohkura T, Yoshikawa S, Sonoda T, Miyamachi H, Yakiwara H, Hirano S, Saito K, Suemine K, Goto S, Ikegami T, Kato K, Matsusue S, Kohno T, et al.: The repeated seismic survey 2010 in Sakurajima Volcano, south Kyushu, Japan, the second round. Ann Disaster Prev Res Inst, Kyoto Univ 2011, 54: 195–208.Google Scholar
- Yamaoka K, Kunitomo T, Miyakawa K, Kobayashi K, Kumazawa M: A trial for monitoring temporal variation of seismic velocity using an ACROSS system. Island Arc 2001, 10: 336–347. 10.1046/j.1440-1738.2001.00332.xView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.