Surface wave group velocity in the Osaka sedimentary basin, Japan, estimated using ambient noise cross-correlation functions
© The Author(s) 2017
Received: 27 February 2017
Accepted: 31 July 2017
Published: 15 August 2017
KeywordsOsaka sedimentary basin Velocity structure model Seismic interferometry Surface wave Group velocity
The Osaka basin in western Japan is a sedimentary basin filled by the Plio-Pleistocene Osaka Group, which is 1–3 km thick. The Osaka Group overlies Miocene and pre-Tertiary basement rocks and is discordantly overlain by terrace and alluvial deposits (e.g., Itihara et al. 1997). Ground motions in the Osaka basin are remarkably amplified and prolonged during moderate to large earthquakes (e.g., Hatayama et al. 1995; Furumura and Koketsu 1998; Asano et al. 2016b; Iwata et al. 2016). To simulate or predict the ground motions of damaging earthquakes quantitatively, a reliable velocity structure and source models for future earthquakes are indispensable. The velocity structure of the Osaka basin has been investigated extensively using geophysical and geological techniques such as gravity anomaly measurements (e.g., Nakagawa et al. 1991; Inoue et al. 1998), refraction and reflection surveys (e.g., Toriumi et al. 1990; Kagawa et al. 1990; Horike et al. 1996), offshore seismic air gun reflection surveys (e.g., Iwasaki et al. 1994; Iwabuchi et al. 2000; Ito et al. 2001), boring explorations (e.g., Ikebe et al. 1970; Yoshikawa et al. 1998; Inoue et al. 2013), microtremor measurements (e.g., Kagawa et al. 1998; Uebayashi 2003; Yoshimi 2012; Minami et al. 2014), and strong motion observations (e.g., Hatayama et al. 1995; Toki et al. 1995). Based on the results obtained using these techniques and ground motion simulations for observed moderate events, three-dimensional velocity structure models of the Osaka basin have been developed and improved over several decades (e.g., Kagawa et al. 1993, 2004; Horikawa et al. 2003; Iwata et al. 2008; Iwaki and Iwata 2011; Sekiguchi et al. 2013). Although many types of surveys have been conducted, more direct information and validation on the S-wave velocity structure is still necessary to improve the velocity structure model because the available constraints from those surveys are not distributed uniformly over the basin.
Seismic interferometry, which employs continuous ambient noise or microtremor records, is used to characterize seismic wave propagation in the Earth and has been widely applied in pure and engineering seismology on various scales (e.g., Shapiro and Campillo 2004; Sabra et al. 2005; Bensen et al. 2007; Yamanaka et al. 2010; Seats et al. 2012; Denolle et al. 2014; Hayashida et al. 2014; Lin et al. 2014; Viens et al. 2016). Ma et al. (2008) tested two community velocity models for the Los Angeles area that were developed by the Southern California Earthquake Center (SCEC) by comparing observed inter-station Green’s functions extracted by correlating the vertical components of ambient seismic noise recorded at 56 broadband stations with those simulated by the finite element method. Chimoto and Yamanaka (2011) conducted tomographic analysis to map surface wave group velocities in the southern part of the Kanto area of Japan with a cell interval of 0.125°. They used the observed group velocity data from inter-station Green’s functions estimated by means of seismic interferometry analysis of continuous microtremor data. Denolle et al. (2014), Boué et al. (2016), and Viens et al. (2016) also analyzed basin amplification in the Kanto basin in, the Tokyo metropolitan area of Japan, using ambient noise Green’s functions.
The target area of this paper is the Osaka sedimentary basin, southwest Japan, as stated in the beginning of this section. We conduct temporary seismic observations to record ambient noise or microtremors continuously at 15 sites in the Osaka basin, and we applied the seismic interferometry technique to this data set. We focus on wave propagation in the frequency range of 0.1–0.5 Hz considering characteristic ground motion amplification in the target area and the signal-to-noise ratio of signals obtained by the seismic interferometry. We compare the observed inter-station cross-correlation functions with theoretical Green’s functions simulated using a three-dimensional velocity structure model of the Osaka basin. We then estimate the spatial distribution of the surface wave group velocities using inter-station cross-correlation functions, and we examine the differences between group velocities estimated by this analysis and theoretical dispersion curves using the present velocity structure model.
Inter-station cross-correlation functions in the Osaka basin
Temporary continuous microtremor observation
Temporary observation sites
Obtained inter-station cross-correlation functions
The transverse component dominated the particle motion on the T–R plane (horizontal plane) due to transverse force (Fig. 2c, f). We inferred that the predominant wave packet or phase in the T–T component is the fundamental mode of the Love wave. Because no other significant wave packet was visible in the obtained T–T signals, the higher modes of the Love wave were not strongly excited in this frequency range; thus, it would have existed only at higher frequencies. The outstanding fundamental Love wave is consistent with the observational and theoretical study by Hatayama et al. (1995). They reported that the fundamental mode of the Love wave predominant in the later part of the observed ground motion in the Osaka basin was excited by large, deep earthquakes and that the first higher mode of the basin-induced Love wave cannot exist in frequencies less than 0.5 Hz in the central part of the basin. On the contrary, Boué et al. (2016) reported clear excitation of the first and second higher modes of the Love wave in the Kanto basin, southeast Japan, based on ambient noise Green’s functions in the frequency range of 0.25–0.5 Hz. The Kanto basin contains thick Neogene sediments of the Miura group above pre-Neogene bedrock (Ito et al. 2016). The S-wave velocity inside the basin gradually increases with depth (e.g., Takemura et al. 2015). The Osaka basin is smaller than the Kanto basin and has a clear unconformity at the sediment–bedrock boundary with a large jump in S-wave velocity. The S-wave velocity in the sediments is less than 1.0 km/s (e.g., Sekiguchi et al. 2016). The difference of the velocity structure in the sedimentary basin would cause a difference in excitation of the modes.
Validation of present velocity structure model in the Osaka basin
Simulation of Green’s function using the finite difference method
Validation of the velocity structure model is important for improving the accuracy and reliability of scenario-based strong motion prediction in sedimentary basins and plains. A traditional method of validating a model is numerical simulation of ground motion excited by small to large earthquakes (e.g., Aagaard et al. 2008; Aoi et al. 2008; Iwaki and Iwata 2010; Dhakal and Yamanaka 2013; Maufroy et al. 2015; Asano et al. 2016b; Guo et al. 2016; Taborda et al. 2016). For modeling a real earthquake, the source model and wave propagation outside the target area should be examined. The azimuthal coverage of sources depends on the seismicity of the target area. Currently, inter-station Green’s functions are used to validate three-dimensional seismic velocity structure models as an alternative to ground motion records of real earthquakes (e.g., Ma et al. 2008; Asano et al. 2011; Gao and Shen 2012). By using waveform information of inter-station Green’s functions, we can obtain good spatial coverage of the ray path across the basin, and we can focus on wave propagation characteristics inside the basin. These points are significant for using inter-station Green’s functions in the validation of velocity structure models.
Theoretical inter-station Green’s functions were simulated using the present three-dimensional velocity structure model UMC2013 (Sekiguchi et al. 2013, 2016) to assess the effectiveness in the present model in explaining the observed characteristics of surface wave propagation in the Osaka basin. This velocity structure model was developed on the basis of geological strata, 60 reflection surveys, 89 deep boring exploration logs, phase–velocity curves obtained from 65 microtremor array measurements, dominant frequencies of microtremor H/V spectra at 110 sites, and PS–P time measurements obtained from receiver function analysis of event records at 82 strong motion stations (Sekiguchi et al. 2016). The velocity model is a function of burial depth and depositional age. The minimum P-wave and S-wave velocities of the model were 1.5 and 0.25 km/s, respectively. A detailed description of this model has been given by Sekiguchi et al. (2016). This velocity structure model was used by Asano et al. (2016b) to simulate ground motions during an M W 5.8 inland crustal earthquake that occurred on Awaji Island near the western boundary of the Osaka basin.
Theoretical Green’s functions were computed by using the finite difference method (FDM). The FDM simulation technique used and the implementation of the UMC2013 model were the same as those described in Asano et al. (2016b). Essentially, a staggered-grid FDM scheme in a velocity–stress formulation with fourth-order accuracy in space and second-order accuracy in time was used to solve elastodynamic wave equations. A zero-stress formulation was introduced for the free surface boundary condition at the top of the model space (e.g., Levander 1988; Graves 1996). A multi-axial perfectly matched layer (PML) was applied to the model boundaries, except for the free surface, to avoid non-physical reflections (Meza-Fajardo and Papageorgiou 2008; Zeng et al. 2011). The grid thickness of the PML domain was set to 10 grids. Anelastic attenuation in the medium was included in the form of a linear frequency-dependent Q operator Q(f) = Q 0(f/f 0) following the method proposed by Graves (1996). The quality factor Q 0 at the reference frequency f 0 = 0.2 Hz was determined from Q 0 = 0.3 V S for the sediments, where V S is the S-wave velocity (Asano et al. 2016b). The source was given by a single force excited on the ground surface at each station. The source time function was represented by a pseudo delta function (Herrmann 1979). Three cases consisting of vertical, radial, and transverse single forces were simulated for each source location.
The FDM model space, occupying an area of 80 km (E–W) × 70 km (N–S) in and adjacent to the Osaka sedimentary basin and corresponding to the geographical area shown in Fig. 1, extends to a depth of 25.5 km below the ground surface, or the free surface. The model was discretized using a uniform 0.05 km grid along the horizontal and vertical axes with the number of grid points at 1601 × 1401 × 512 = 1,148,416,512. Because the elevation inside the land area of the Osaka basin is less than one grid size, our simulation did not consider surface topography. Three-dimensional wave propagation was simulated for 180 s after the origin time at increments of 0.0025 s. The total number of time steps in this simulation was 72,000.
Comparison with synthetic Green’s functions
Surface wave group velocity tomography
Results and discussion
In contrast, cell (2, 5) exhibited a large discrepancy between the estimated and theoretical dispersion curves in the middle period range. One possible explanation for this discrepancy is that the accuracy of the velocity structure was insufficient owing to the limited amount of information available for use in developing the present model in that area. In addition, the actual bedrock depth might be deeper than the present velocity structure model. The observed period of the Airy phase, which shows the minimum group velocity, was approximately 4 s for the Love wave in this cell; thus, the actual depth of the bedrock is between 0.5 and 1.0 km. However, possible reasons that might affect the estimation of group velocity itself must be considered. Few ray paths crossed this cell because it is close to the edge of the study area, and the dispersion curve constructed from the ambient noise cross-correlation was averaged over several cells along the station-to-station path. The assumption of straight ray paths in the tomographic analysis would result in some error in estimating the group velocity when significant spatial variation is present in the seismic wave velocity.
For future reconstruction of the three-dimensional velocity structure model in the Osaka sedimentary basin, utilization of waveform information from inter-station Green’s functions through waveform modeling is a direct and straightforward method because it can naturally include three-dimensional effects on wave propagation such as ray bending, multipathing, mode conversion, and generation of basin edge-induced surface waves. Nevertheless, surface wave group velocity tomography is also a useful tool for identifying area in which further effort should be made to improve the current velocity structure model by comparing inverted and theoretical dispersion curves. The number of ray paths for the Rayleigh wave used in our work is about two-thirds of that for the Love wave because of the difficulty in identifying the fundamental mode. Because mode misidentification is critical for the Rayleigh wave, as discussed by Boaga et al. (2013), and the T–T cross-correlation function (Love wave) dominates the data set in the Osaka basin, it is better to emphasize the Love wave rather than the Rayleigh wave to analyze the velocity structure model. It is widely accepted that the combined use of a variety of observation information leads to a robust model because each survey technique has unique advantages and weaknesses. We believe the inter-station Green’s functions and surface wave group velocity data will contribute to reconstruction of the three-dimensional velocity structure model of the Osaka sedimentary basin as well as other existing survey results.
Inter-station cross-correlation functions estimated using continuous ambient noise or microtremor records observed at 15 temporary stations were used to extract the seismic wave propagation characteristics of the Osaka sedimentary basin. Cross-correlations between all of the possible pairs were calculated and stacked to obtain a year-long data sequence. The resulting cross-correlation functions were found to have Rayleigh wave signals in the vertical and radial components and Love wave signals in the transverse component. Theoretical Green’s functions calculated by the FDM using the latest three-dimensional velocity structure model reproduced the characteristics of the observed inter-station cross-correlation functions. Three-dimensional effects on surface wave propagation emerged as contributions of the Love wave in the radial component. The measured time lag between the observed and theoretical Green’s functions was less than 2 s for most station pairs, which is less than the wave period of interest in the target frequency range of 0.125–0.250 Hz.
The group delay time of surface waves at each period was estimated using the multiple filter analysis technique. We applied group velocity tomography to the group delay time data. The estimated group velocity for longer periods of 5–8 s exhibited significant spatial variation within the basin that was roughly consistent with the bedrock depth distribution. The group velocity for shorter periods of 2–3 s was almost constant over the studied area. A comparison of the estimated dispersion curve and the theoretical dispersion curve calculated from the present velocity structure model would help to identify areas in which further improvement in the model is necessary.
KA participated in the temporary observations, analyzed the data, and drafted the manuscript. TI participated in the design of the study and organized the temporary observations. HS participated in the design of the study and prepared the three-dimensional velocity structure model. KS, KM, SA, and TK participated in conducting the temporary observations. All of the authors read and approved the final manuscript.
The authors thank Ichiro Matsuo, Naoji Koizumi, and Yasuhiro Umeda for helping to conduct temporary observations in the Osaka basin. In addition, the authors are grateful to the Crisis Management Office of Osaka Prefectural Government, Suita City Fire Department, Matsubara City Office, Kishiwada City Office, Izumi City Office, Sakai City Office, Sakai City Fire Bureau, Osaka Sayama City Office, Yao City Office, Kadoma City Office, Toyonaka City Office, Geo-Research Institute, National Research Institute for Earth Science and Disaster Resilience, and Geological Survey of Japan for cooperation in temporary observations. The temporary observations were conducted as a part of the Comprehensive Research on the Uemachi Fault Zone funded by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan. The Cray XE6 and XC40 supercomputers of the Academic Center for Computing and Media Studies of Kyoto University were used, and Generic Mapping Tools (Wessel and Smith 1998) was used to draw the figures. Careful reviews and comments by Marine Denolle, an anonymous reviewer, and guest editor Francisco J. Sanchez-Sesma were quite helpful for improving the manuscript. This study was partly supported by the Earthquake and Volcano Hazards Observation and Research Program of MEXT and a Grant-in-Aid for Young Scientist (B) 25750146 by the Japan Society for the Promotion of Science (JSPS).
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Aagaard BT, Brocher TM, Dolenc D, Dreger D, Graves RW, Harmsen S, Hartzell S, Larsen S, Zoback ML (2008) Ground-motion modeling of the 1906 San Francisco earthquake. Part I: validation using the 1989 Loma Prieta earthquake. Bull Seismol Soc Am 98(2):989–1011. doi:10.1785/0120060409 View ArticleGoogle Scholar
- Akaike H (1980) Likelihood and the Bayes procedure. Trab Estad Invest Oper 31(1):143–166. doi:10.1007/BF02888350 View ArticleGoogle Scholar
- Aoi S, Honda R, Morikawa N, Sekiguchi H, Suzuki H, Hayakawa Y, Kunugi T, Fujiwara H (2008) Three-dimensional finite difference simulation of long-period ground motions for the 2003 Tokachi-oki, Japan, earthquake. J Geophys Res 113(7):B07302. doi:10.1029/2007JB005452 Google Scholar
- Asano K, Iwaki A, Iwata T (2011) Estimation of interstation Green’s functions in the long-period range (2–10 s) from continuous records of F-net broadband seismograph network in southwestern Japan. In: Proceedings of the 4th IASPEI/IAEE international symposium on effects of surface geology on seismic motion, Santa Barbara, 23–26 August 2011Google Scholar
- Asano K, Iwata T, Sekiguchi H (2012) Application of seismic interferometry in the Osaka basin for validating the three-dimensional basin velocity structure model. In: Proceedings of the 15th world conference on earthquake engineering, Lisbon, 24–28 September 2012Google Scholar
- Asano K, Iwata T, Sekiguchi H, Somei K, Miyakoshi K, Aoi S, Kunugi T (2016a) Surface wave group velocity tomography in the Osaka sedimentary basin, Japan, using ambient noise cross-correlation functions. In: Proceedings of the 5th IASPEI/IAEE international symposium on effects of surface geology on seismic motion, Taipei, 15–17 August 2016Google Scholar
- Asano K, Sekiguchi H, Iwata T, Yoshimi M, Hayashida T, Saomoto H, Horikawa H (2016b) Modelling of wave propagation and attenuation in the Osaka sedimentary basin, western Japan, during the 2013 Awaji Island earthquake. Geophys J Int 204(3):1678–1694. doi:10.1093/gji/ggv543 View ArticleGoogle Scholar
- Bensen GD, Ritzwoller MH, Barmin MP, Levshin AL, Lin F, Moschetti MP, Shapiro NM, Yang Y (2007) Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophys J Int 169(3):1239–1260. doi:10.1111/j.1365-246X.2007.03374.x View ArticleGoogle Scholar
- Boaga J, Cassiani G, Strobbia CL, Vignoli G (2013) Mode misidentification in Rayleigh waves: ellipticity as a cause and a cure. Geophysics 78(4):EN17–EN18. doi:10.1190/GEO2012-0194.1 View ArticleGoogle Scholar
- Boué P, Denolle M, Hirata N, Nakagawa S, Beroza GC (2016) Beyond basin resonance: characterizing wave propagation using a dense array and the ambient seismic field. Geophys J Int 206(2):1261–1272. doi:10.1093/gji/ggw205 View ArticleGoogle Scholar
- Chimoto K, Yamanaka H (2011) Tomographic analysis of surface wave slowness estimated with seismic interferometric processing of continuous microtremor data in the southern Kanto area, Japan. BUTSURI-TANSA (Geophys Explor) 64(5):331–343. doi:10.3124/segj.64.331 (in Japanese with English abstract) View ArticleGoogle Scholar
- Denolle MA, Miyake H, Nakagawa S, Hirata N, Beroza GC (2014) Long-period seismic amplification in the Kanto Basin from the ambient seismic field. Geophys Res Lett 41(7):2319–2325. doi:10.1002/2014GL059425 View ArticleGoogle Scholar
- Dhakal Y, Yamanaka H (2013) An evaluation of 3-D velocity models of the Kanto basin for long-period ground motion simulations. J Seismol 17(3):1073–1102. doi:10.1007/s10950-013-9373-4 View ArticleGoogle Scholar
- Dziewonski A, Bloch S, Landisman M (1969) A technique for the analysis of transient seismic signals. Bull Seismol Soc Am 59(1):427–444Google Scholar
- Furumura T, Koketsu K (1998) Specific distribution of ground motion during the 1995 Kobe earthquake and its generation mechanism. Geophys Res Lett 25(6):785–788. doi:10.1029/98GL50418 View ArticleGoogle Scholar
- Gao H, Shen Y (2012) Validation of shear-wave velocity models of the Pacific Northwest. Bull Seismol Soc Am 102(6):2611–2621. doi:10.1785/0120110336 View ArticleGoogle Scholar
- Graves RW (1996) Simulating seismic wave propagation in 3D elastic media using staggered-grid finite differences. Bull Seismol Soc Am 86(4):1091–1106Google Scholar
- Guo Y, Koketsu K, Miyake H (2016) Propagation mechanism of long-period ground motions for offshore earthquakes along the Nankai trough: effects of the accretionary wedge. Bull Seismol Soc Am 106(3):1176–1197. doi:10.1785/0120150315 View ArticleGoogle Scholar
- Hatayama K, Matsunami K, Iwata T, Irikura K (1995) Basin-induced Love waves in the eastern part of the Osaka basin. J Phys Earth 43(2):131–155. doi:10.4294/jpe1952.43.131 View ArticleGoogle Scholar
- Hayashida T, Yoshimi M, Horikawa H (2014) Estimation of surface wave group velocity beneath the Chukyo area, Japan. Zisin 2 (J Seismol Soc Jpn) 66(4):127–145. doi:10.4294/zisin.66.127 (in Japanese with English abstract) Google Scholar
- Herrmann RB (1979) SH-wave generation by dislocation source—a numerical study. Bull Seismol Soc Am 69(1):1–15Google Scholar
- Horikawa H, Mizuno K, Ishiyama T, Satake K, Sekiguchi H, Kase Y, Sugiyama Y, Yokota H, Suehiro M, Yokokura T, Iwabuchi Y, Kitada N, Pitarka A (2003) A three-dimensional subsurface structure model beneath the Osaka sedimentary basin, southwest Japan, with fault-related structural discontinuities. Ann Report Active Fault Paleoearthquake Res Geol Survey Japan 3:225–259 (in Japanese with English abstract) Google Scholar
- Horike M, Takeuchi Y, Imai S, Fuzita T, Yokota H, Noda T, Ikawa T (1996) Survey of the subsurface structure in the east of Osaka basin. Zisin 2 (J Seismol Soc Jpn) 49(2):193–203. doi:10.4294/zisin1948.49.2_193 (in Japanese with English abstract) Google Scholar
- Ikebe N, Iwatsu J, Takenaka J (1970) Quaternary geology of Osaka with special reference to land subsidence. J Geosci Osaka City Univ 13:39–98Google Scholar
- Inoue N, Nakagawa K, Ryoki K (1998) Gravity anomalies and basement structure in Osaka plain. BUTSURI-TANSA (Geophys Explor) 51(1):1–16 (in Japanese with English abstract) Google Scholar
- Inoue N, Kitada N, Takemura K, Fukuda K, Emura T (2013) Three-dimensional subsurface structure model of Kansai International Airport by integration of borehole data and seismic profiles. Geotech Geol Eng 31(3):881–890. doi:10.1007/s10706-012-9568-4 View ArticleGoogle Scholar
- Itihara M, Yoshikawa S, Kamei T (1997) The Pliocene–Pleistocene boundary in Japan: the Osaka Group, Kinki district. In: Van Couvering JA (ed) The Pleistocene boundary and beginning of the Quaternary. World and regional geology, vol 9. Cambridge University Press, Cambridge, pp 239–243. doi:10.1017/CBO9780511585760.026 Google Scholar
- Ito Y, Takemura K, Kawabata D, Tanaka Y, Nakaseko K (2001) Quaternary tectonic warping and strata formation in the southern Osaka Basin inferred from reflection seismic interpretation and borehole sequences. J Asian Earth Sci 20(1):45–58. doi:10.1016/S1367-9120(01)00019-0 View ArticleGoogle Scholar
- Ito M, Kameo K, Satoguchi Y, Masuda F, Hiroki Y, Takano O, Nakajima T, Suzuki N (2016) Neogene–Quaternary sedimentary successions. In: Moreno T, Wallis S, Kojima T, Gibbons W (eds) The geology of Japan. Geological Society of London, London, pp 309–337Google Scholar
- Iwabuchi Y, Nishikawa H, Noda N, Yukimatsu T, Taga M, Miyano M, Sakai K, Fukazawa M (2000) Basement and active structures revealed by the seismic reflection survey in Osaka bay. Rep Hydrogr Res 36:1–23 (in Japanese with English abstract) Google Scholar
- Iwaki A, Iwata T (2010) Simulation of long-period ground motion in the Osaka sedimentary basin: performance estimation and the basin structure effects. Geophys J Int 181(2):1062–1076. doi:10.1111/j.1365-246X.2010.04556.x Google Scholar
- Iwaki A, Iwata T (2011) Estimation of three-dimensional boundary shape of the Osaka sedimentary basin by waveform inversion. Geophys J Int 186(3):1255–1278. doi:10.1111/j.1365-246X.2011.05102.x View ArticleGoogle Scholar
- Iwasaki Y, Kagawa T, Sawada S, Matsuyama N, Ohshima K, Ikawa T, Onishi M (1994) Basement structure by air-gun reflection survey in Osaka Bay, Southwest Japan. Zisin 2 (J Seismol Soc Jpn) 46(4):395–403. doi:10.4294/zisin1948.46.4_395 (in Japanese with English abstract) Google Scholar
- Iwata T, Kagawa T, Petukhin A, Ohnishi Y (2008) Basin and crustal velocity structure models for the simulation of strong ground motions in the Kinki area, Japan. J Seism 12(2):223–234. doi:10.1007/s10950-007-9086-7 View ArticleGoogle Scholar
- Iwata T, Kubo H, Asano K, Sato K, Aoi S (2016) Long-period ground motion characteristics and simulations in the Osaka basin during the 2011 great Tohoku earthquake. In: Proceedings of the 5th international symposium for effects of surface geology on seismic motion, Taipei, 15–17 August, 2016Google Scholar
- Kagawa T, Sawada S, Iwasaki Y, Emi S (1990) Underground velocity structure of Osaka basin upon explosion refraction data. Zisin 2 (J Seismol Soc Jpn) 43(4):527–537. doi:10.4294/zisin1948.51.1_31 (in Japanese with English abstract) Google Scholar
- Kagawa T, Sawada S, Iwasaki Y, Nanjo A (1993) Modeling the deep sedimentary structure in the Osaka basin. In: Proceedings of the 22nd JSCE earthquake engineering symposium, Kyoto, 26–28 July 1993. doi:10.2208/proee1957.22.199 (in Japanese)
- Kagawa T, Sawada S, Iwasaki Y, Nanjo A (1998) S-wave velocity structure model of the Osaka sedimentary basin derived from microtremor array observations. Zisin 2 (J Seismol Soc Jpn) 51(1):31–40. doi:10.4294/zisin1948.51.1_31 (in Japanese with English abstract) Google Scholar
- Kagawa T, Zhao B, Miyakoshi K, Irikura K (2004) Modeling of 3D basin structures for seismic wave simulations of the Osaka basin. Bull Seismol Soc Am 94(4):1353–1368. doi:10.1785/012003165 View ArticleGoogle Scholar
- Lawson CL, Hanson RJ (1974) Solving least squares problems. Prentice-Hall, Englewood CliffsGoogle Scholar
- Lees JM, Crosson RS (1989) Tomographic inversion for three-dimensional velocity structure at Mount St. Helens using earthquake data. J Geophys Res 94(B5):5716–5728. doi:10.1029/JB094iB05p05716 View ArticleGoogle Scholar
- Levander AR (1988) Fourth-order finite-difference P-SV seismograms. Geophysics 53(11):1425–1436. doi:10.1190/1.1442422 View ArticleGoogle Scholar
- Lin F-C, Moschetti MP, Ritzwoller MH (2008) Surface wave tomography of the western United States from ambient seismic noise: Rayleigh and Love wave phase velocity map. Geophys J Int 173(1):281–298. doi:10.1111/j.1365-246X.2008.03720.x View ArticleGoogle Scholar
- Lin F-C, Tsai TC, Schmandt B (2014) 3-D crustal structure of the western United States: application of Rayleigh-wave ellipticity extracted from noise cross-correlations. Geophys J Int 198(2):656–670. doi:10.1093/gji/ggu160 View ArticleGoogle Scholar
- Ma S, Prieto GA, Beroza GC (2008) Testing community velocity models for southern California using the ambient seismic field. Bull Seismol Soc Am 98(6):2694–2714. doi:10.1785/0120080947 View ArticleGoogle Scholar
- Maufroy E, Chaljub E, Hollender F, Kristek J, Moczo P, Klin P, Priolo E, Iwaki A, Iwata T, Etienne V, De Martin F, Theodoulidis NP, Manakou M, Guyonnet-Benaize C, Pitilakis K, Bard P-Y (2015) Earthquake ground motion in the Mygdonian basin, Greece: the E2VP verification and validation of 3D numerical simulation up to 4 Hz. Bull Seismol Soc Am 105(3):1398–1418. doi:10.1785/0120140228 View ArticleGoogle Scholar
- Meza-Fajardo KC, Papageorgiou AS (2008) A nonconvolutional, splitfield, perfectly matched layer for wave propagation in isotropic and anisotropic elastic media: stability analysis. Bull Seismol Soc Am 98(4):1811–1836. doi:10.1785/0120070223 View ArticleGoogle Scholar
- Minami Y, Mizuochi Y, Matsuoka T, Haraguchi T, Motoki K (2014) Deep S-wave velocity structure in Osaka plains urban area estimated by microtremor survey method. J Jpn Soc Eng Geol 55(3):110–117. doi:10.5110/jjseg.55.110 (in Japanese with English abstract) View ArticleGoogle Scholar
- Nakagawa K, Ryoki K, Muto N, Nishimura S, Ito K (1991) Gravity anomaly map and inferred basement structure in Osaka Plain, Central Kinki, Southwest Japan. J Geosci Osaka City Univ 34:103–117Google Scholar
- Sabra KG, Gerstoft P, Roux P, Kuperman WA, Fehler MC (2005) Extracting time-domain Green’s function estimates from ambient seismic noise. Geophys Res Lett 32(3):L03310. doi:10.1029/2004GL021862 View ArticleGoogle Scholar
- Saito M (1988) DISPER80: a subroutine package for the calculation of seismic normal mode solutions. In: Doornbos DJ (ed) Seismological algorithms: computational methods and computer programs. Academic Press, LondonGoogle Scholar
- Seats KJ, Lawrence JF, Prieto GA (2012) Improved ambient noise correlation functions using Welch’s method. Geophys J Int 188(2):513–523. doi:10.1111/j.1365-246X.2011.05263.x View ArticleGoogle Scholar
- Sekiguchi H, Yoshimi M, Asano K, Horikawa H, Saomoto H, Hayashida T, Iwata T (2013) Newly developed 3D velocity structure model of the Osaka sedimentary basin. In: Abstracts of Japan Geoscience Union meeting, Chiba, 19–24 May 2013Google Scholar
- Sekiguchi H, Asano K, Iwata T, Yoshimi M, Horikawa H, Saomoto H, Hayashida T (2016) Construction of 3D velocity structure model of Osaka sedimentary basin. In: Proceedings of the 5th international symposium for effects of surface geology on seismic motion, Taipei, 15–17 August, 2016Google Scholar
- Shapiro NM, Campillo M (2004) Emergence of broadband Rayleigh waves from correlations of the ambient seismic noise. Geophys Res Lett 31(7):L07614. doi:10.1029/2004GL019491 View ArticleGoogle Scholar
- Taborda R, Azizzadeh-Roodpish S, Khoshnevis N, Cheng K (2016) Evaluation of the southern California seismic velocity model through simulation of recorded events. Geophys J Int 205(3):1342–1364. doi:10.1093/gji/ggw085 View ArticleGoogle Scholar
- Takagi R, Nakahara H, Kono T, Okada T (2014) Separating body and Rayleigh waves with cross terms of the cross-correlation tensor of ambient noise. J Geophys Res 119(3):2005–2018. doi:10.1002/2013JB010824 View ArticleGoogle Scholar
- Takemura S, Akatsu M, Masuda K, Kajikawa K, Yoshimoto K (2015) Long-period ground motions in a laterally inhomogeneous large sedimentary basin: observations and model simulations of long-period surface waves in the northern Kanto Basin, Japan. Earth Planets Space 67:33. doi:10.1186/s40623-015-0201-7 View ArticleGoogle Scholar
- Toki K, Irikura K, Kagawa T (1995) Strong motion records in the source area of the Hyogoken-Nambu earthquake, January 17, 1995, Japan. J Nat Disas Sci 16(2):23–30Google Scholar
- Toriumi I, Takeuchi Y, Ohba S, Horike M, Inoue Y, Baba K (1990) Underground structure in the Osaka plain by Hokko explosions. Zisin 2 (J Seismol Soc Jpn) 43(3):373–378. doi:10.4294/zisin1948.43.3_373 (in Japanese with English abstract) Google Scholar
- Uebayashi H (2003) Extrapolation of irregular subsurface structures using the horizontal-to-vertical spectral ratio of long-period microtremors. Bull Seimol Soc Am 93(2):570–582. doi:10.1785/0120020137 View ArticleGoogle Scholar
- Viens L, Koketsu K, Miyake H, Sakai S, Nakagawa S (2016) Basin-scale Green’s functions from the ambient seismic field recorded by MeSO-net stations. J Geophys Res 121(4):2507–2520. doi:10.1002/2016JB012796 View ArticleGoogle Scholar
- Wapenaar K, Fokkema J (2006) Green’s function representations for seismic interferometry. Geophysics 71(4):SI33–SI46. doi:10.1190/1.2213955 View ArticleGoogle Scholar
- Wessel P, Smith WHF (1998) New, improved version of generic mapping tools released. EOS Trans Am Geophys Union 79:579View ArticleGoogle Scholar
- Yamanaka H, Chimoto K, Moroi T, Ikeura T, Koketsu K, Sakaue M, Nakai S, Sekiguchi T, Oda Y (2010) Estimation of surface-wave group velocity in the southern Kanto area using seismic interferometric processing of continuous microtremor data. BUTSURI-TANSA (Geophys Explor) 63(5):409–425. doi:10.3124/segj.63.409 (in Japanese with English abstract) View ArticleGoogle Scholar
- Yoshikawa S, Mitamura M, Nakagawa K, Nagahashi Y, Iwasaki Y, Echigo T, Tsujie K, Kitada N (1998) Lithostratigraphy and tephrostratigraphy of the Tsumori, Otemae and Hama drilling cores in the Osaka Plain, central Japan. J Geol Soc Jpn 104(7):462–476. doi:10.5575/geosoc.104.462 (in Japanese with English abstract) View ArticleGoogle Scholar
- Yoshimi M (2012) Resolution of the SPAC, CCA, nc-CCA, and V-method for microtremor array survey on deep sedimentary basin—case of the Osaka basin. J Jpn Soc Civil Eng A1 (Struct Eng Earthq Eng) 68(4):I_220–I_226. doi:10.2208/jscejseee.68.I_220 (in Japanese with English abstract) Google Scholar
- Zeng C, Zia J, Miller RD, Tsoflias GP (2011) Application of the multiaxial perfectly matched layer (M-PML) to near-surface seismic modeling with Rayleigh waves. Geophysics 76(3):T43–T52. doi:10.1190/1.3560019 View ArticleGoogle Scholar