To accurately capture ground motion in the Tokyo metropolitan area, we have developed a multi-data integration system that combines a large amount of ground motion data gathered from nationwide strong-motion seismograph networks (K-NET and KiK-net); Metropolitan Seismic Observation network (MeSO-net), which covers the Tokyo metropolitan area with a high density of about 300 observation stations; observation equipment held by private companies; and smartphone-based seismographs. K-NET, KiK-net, and MeSO-net are operated by National Research Institute for Earth Science and Disaster Resilience. The seismic waveform data recorded by MeSO-net, which are based on borehole observations, are one of the most important data sets for this system. To ensure collection of the waveform data, we strengthened the data center functions and made the collected data available to the public. In addition, to estimate the ground motion at the surface, which is important for disaster prevention, from the waveform data of MeSO-net, we carried out temporary seismic and microtremor array observations on the ground surface at each MeSO-net borehole station, and estimated ground amplification characteristics and the S-wave velocity structure. We also developed a smartphone-based seismograph with the aim of realizing seismic observations for tens of thousands of sites in the future. We recruited monitors to deploy the smartphone seismometers in the Tokyo metropolitan area, and developed a function to notify monitors of the results of a rough evaluation of the soundness of buildings based on observation data acquired during an earthquake. Furthermore, we have developed a Tokyo metropolitan area version of Kyoshin Monitor, the strong motion monitor system, with which the current ground motion in the Tokyo metropolitan area can be captured in real time by integrating and visualizing observation data from K-NET, KiK-net, and MeSO-net on a map on the website. We can capture the propagation of the ground motion in detail directly from the high-density data set integrated from these three networks. In addition, we also integrated data from Super-Dense Real-time Monitoring of Earthquakes (SUPREME) network of Tokyo Gas Co., Ltd., which operates about 4,000 observation stations in the Tokyo metropolitan area, after applying a time correction. We verified the integration method by reproducing the ground motion in the Tokyo metropolitan area during the 2011 Tohoku earthquake. The study findings have made it clear that the ground motion in the Tokyo metropolitan area can be captured in more detail by the integration of data produced by the public and private sectors.

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