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.

1. [1] 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, doi: 10.20965/jdr.2017.p0233, 2017.
2. [2] T. Maeda, H. Fujiwara, T. Hayakawa, S. Shimono, and S. Akagi, “Cluster Analysis of Long-Period Ground-Motion Simulation Data with Application to Nankai Trough Megathrust earthquake Scenarios,” J. Disaster Res., Vol.13, No.2, pp. 254-261, doi: 10.20965/jdr.2018.p0254, 2018.
3. [3] H. Hotelling, “Analysis of a complex of statistical variables into principal components,” J. of Educational Psychology, Vol.24, pp. 417-441, 1933.
4. [4] J. B. MacQueen, “Some Methods for classification and Analysis of Multivariate Observations,” Proc. of 5th Berkeley Symp. on Mathematical Statistics and Probability, Vol.1, pp. 281-297, University of California Press, 1967.
5. [5] T. Maeda, A. Iwaki, N. Morikawa, R. Imai, S. Aoi, and H. Fujiwara, “Approach to broaden the period-range of long-period ground motion evaluation based on theoretical method,” Japan Geoscience Union Meeting, SSS25-20, 2015.
6. [6] T. Maeda, A. Iwaki, N. Morikawa, R. Imai, S. Aoi, and H. Fujiwara, “Long-period ground motion evaluation for the Sagami Trough megathrust earthquakes,” Japan Geoscience Union Meeting, SSS25-5, 2016.
7. [7] S. Aoi, T. Hayakawa, and H. Fujiwara, “Ground motion simulator: GMS,” Butsuri Tansa., Vol.57, pp. 651- 666, 2004 (in Japanese with English abstract).
8. [8] Earthquake Research Committee, “Report: ‘National Seismic hazard Maps for Japan (2018)’,” https://www.jishin.go.jp/evaluation/seismic_hazard_map/shm_report/ (in Japanese) [accessed January 29, 2019]
9. [9] National Research Institute for Earth Science and Disaster Resilience, J-SHIS Map, http://www.j-shis.bosai.go.jp/map/?lang=en [accessed January 29, 2019]
10. [10] Earthquake Research Committee, “Long-period ground motion hazard maps for Japan (2012),” https://www.jishin.go.jp/evaluation/seismic_hazard_map/lpshm/12_choshuki/ (in Japanese) [accessed January 29, 2019]
11. [11] Earthquake Research Committee, “Evaluation of long period ground motion (2016) – examination of the Sagami Trough earthquake –,” https://www.jishin.go.jp/evaluation/seismic_hazard_map/lpshm/16_choshuki/ (in Japanese) [accessed January 29, 2019]
12. [12] Earthquake Research Committee, “Shallow-deep combined velocity structure model for Kanto region,” https://www.jishin.go.jp/evaluation/seismic_hazard_map/underground_model/integration_model_kanto/ (in Japanese) [accessed January 29, 2019]
13. [13] P. Wessel and W. H. F. Smith, “New version of the Generic Mapping Tools released,” EOS Trans., American Geophysical Union, Vol.76, p. 329, 1995.
14. [14] http://ecom-plat.jp/ [accessed January 29, 2019]
15. [15] http://ecom-plat.jp/k-cloud/index.php [accessed January 29, 2019]