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JDR Vol.12 No.2 pp. 233-240
(2017)
doi: 10.20965/jdr.2017.p0233

Paper:

Seismic Hazard Visualization from Big Simulation Data: Cluster Analysis of Long-Period Ground-Motion Simulation Data

Takahiro Maeda and Hiroyuki Fujiwara

National Research Institute for Earth Science and Disaster Resilience
3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan

Corresponding author

Received:
October 25, 2016
Accepted:
February 7, 2017
Online released:
March 16, 2017
Published:
March 20, 2017
Keywords:
long-period ground motion, visualization, simulation, parallel distributed processing, clustering
Abstract

This paper describes a method of extracting the relation between the ground-motion characteristics of each area and a seismic source model, based on ground-motion simulation data output in planar form for many earthquake scenarios, and the construction of a parallel distributed processing system where this method is implemented. The extraction is realized using two-stage clustering. In the first stage, the ground-motion indices and scenario parameters are used as input data to cluster the earthquake scenarios within each evaluation mesh. In the second stage, the meshes are clustered based on the similarity of earthquake-scenario clustering. Because the mesh clusters can be correlated to the geographical space, it is possible to extract the relation between the ground-motion characteristics of each area and the scenario parameters by examining the relation between the mesh clusters and scenario clusters obtained by the two-stage clustering. The results are displayed visually; they are saved as GeoTIFF image files. The system was applied to the long-period ground-motion simulation data for hypothetical megathrust earthquakes in the Nankai Trough. This confirmed that the relation between the extracted ground-motion characteristics of each area and scenario parameters is in agreement with the results of ground-motion simulations.

Cite this article as:
T. Maeda and H. Fujiwara, “Seismic Hazard Visualization from Big Simulation Data: Cluster Analysis of Long-Period Ground-Motion Simulation Data,” J. Disaster Res., Vol.12, No.2, pp. 233-240, 2017.
Data files:
References
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Last updated on Dec. 11, 2018