JDR Vol.13 No.3 pp. 440-452
doi: 10.20965/jdr.2018.p0440


Real-Time GNSS Analysis System REGARD: An Overview and Recent Results

Satoshi Kawamoto*1,†, Naofumi Takamatsu*1, Satoshi Abe*1, Kohei Miyagawa*1, Yusaku Ohta*2, Masaru Todoriki*3, and Takuya Nishimura*4

*1Geospatial Information Authority of Japan
1 Kitasato, Tsukuba 305-0811, Japan

Corresponding author

*2Research Center for Prediction of Earthquakes and Volcanic Eruptions, Graduate School of Science, Tohoku University, Sendai, Japan

*3Fujitsu Laboratories Ltd., Kawasaki, Japan

*4Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan

October 31, 2017
January 29, 2018
June 1, 2018
GNSS, real-time GNSS analysis, earthquake modeling, rapid finite-fault model, GEONET

A new real-time Global Navigation Satellite System (GNSS) analysis system named REGARD has been launched to provide finite-fault models for large earthquakes with magnitudes =8 in real time. The finite-fault estimates using GNSS positioning are free from saturation problems and are very robust for modeling large earthquakes. The REGARD system processes ∼1,200 stations of GEONET, and event detection and finite-fault model inversion routines are implemented. Tests for the case of the 2011 Tohoku earthquake (Mw9.0) and a simulated Nankai Trough earthquake (Mw8.7) show that the REGARD system can provide reliable finite-fault models for large earthquakes. Furthermore, operational real-time results for the 2016 Kumamoto earthquake (Mj7.3) demonstrated the capability of this system to model inland earthquakes. These results imply the possibility of improving tsunami simulations and/or hazard information using rapid finite-fault models. Efforts to integrate real-time GNSS with current warning systems are currently being implemented around the world, and the REGARD system will join these systems in the near future.

Cite this article as:
S. Kawamoto, N. Takamatsu, S. Abe, K. Miyagawa, Y. Ohta, M. Todoriki, and T. Nishimura, “Real-Time GNSS Analysis System REGARD: An Overview and Recent Results,” J. Disaster Res., Vol.13, No.3, pp. 440-452, 2018.
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