Open AccessCluster Analysis of the Long-Period Ground-Motion Simulation Data: Application of the Sagami Trough Megathrust Earthquake Scenarios
Author(s) -
Takahiro Maeda,
Hiroyuki Fujiwara,
Sho Akagi,
Toshihiko Hayakawa
Publication year - 2019
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2019.p0435
Subject(s) - geology , seismology , earthquake simulation , peak ground acceleration , strong ground motion , interpolation (computer graphics) , geodesy , cluster analysis , motion (physics) , ground motion , computer science , artificial intelligence , machine learning
A clustering method that classifies earthquake scenarios and the local area on the basis of similarities in the spatial distribution of ground motion was applied to long-period ground-motion data computed by a seismic wave propagation simulation. The simulation utilized a large number of seismic source models and a three-dimensional velocity structure model in which megathrust earthquakes in the Sagami Trough were assumed. The relationship between the clusters, earthquake scenario parameters, and the velocity structure model was examined. In addition, the relationship between the earthquake scenario clusters for a case in which actual strong-motion observation points were treated as a mesh and those for a case in which an entire set of meshes was investigated, and a spatial interpolation method that estimated a ground-motion distribution from strong-motion observation data was examined.