Japan Geoscience Union Meeting 2014

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Oral

Symbol M (Multidisciplinary and Interdisciplinary) » M-AG Applied Geosciences

[M-AG39_1AM2] Special Project for Reducing Vulnerability for Urban Mega Earthquake Disasters

Thu. May 1, 2014 11:00 AM - 12:45 PM 502 (5F)

Convener:*Naoshi Hirata(Earthquake Research Institute, the University of Tokyo), Hiroshi Sato(Earthquake Prediction Research Center, Earthquake Research Institute, The University of Tokyo), Kenji Satake(Earthquake Research Institute, University of Tokyo), Hiroshi Tsuruoka(Earthquake Research Institute, Tokyo Univ.), Muneo Hori(Earthquake Research Institute, The University of Tokyo), Shin'ichi Sakai(Earthquake Research Institute, University of Tokyo), Chair:Naoshi Hirata(Earthquake Research Institute, the University of Tokyo), Shin'ichi Sakai(Earthquake Research Institute, University of Tokyo)

11:00 AM - 11:15 AM

[MAG39-07] A new direction of the MeSO-net

*Naoshi HIRATA1, Shin'ichi SAKAI1, Shigeki NAKAGAWA1, Keiji KASAHARA2, Hisanori KIMURA3, Ryou HONDA4 (1.Earthquake Research Institute, the University of Tokyo, 2.ADEP, 3.NIED, 4.Hot Springs Research Institute of Kanagawa Prefecture)

Keywords:MeSO-net, accelerometer, continuous recording, Autonomous Cooperative data Transfer, automatic event detection, seismic tomography

We have developed the Metropolitan Seismic Observation network (MeSO-net) under the Special Project for Earthquake Disaster Mitigation in Tokyo Metropolitan Area (FY2007-FY2011) and maintain it by the Special Project for Reducing Vulnerability for Urban Mega Earthquake Disasters (FY2012-FY2016), which are supported by MEXT. The network consists of 296 seismic observation stations, from which data are continuously transmitted and recorded at a data management center in ERI. We developed an intelligent data transmission protocol for MeSO-net System, which is referred to as Autonomous Cooperative data Transfer (ACT)(Morita et al., 2010) . As culture noise in urban areas is very high, we use a 20-m-deep shallow borehole to install wide-band accelerometers but a signal-to-noise ratio is still low. A large number with short interval of station configuration helps us to obtain better resolution and high quality seismic data. We are now developing a new automatic data processing function in the MeSO-net: automatic event detection and P- and S-phase picking. We also develop a method to predict ground and building motions from the MeSO-met data.