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Journal Article

An open-source site database of strong-motion stations in Japan: K-NET and KiK-net (v1.0.0)

Authors
/persons/resource/chuanbin

Zhu,  Chuanbin
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/gweather

Weatherill,  Graeme
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/fcotton

Cotton,  Fabrice
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/pilz

Pilz,  M.
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Kwak,  Dong Youp
External Organizations;

Kawase,  Hiroshi
External Organizations;

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No external resources are shared
Fulltext (public)

5005929_2021.pdf
(Postprint), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Zhu, C., Weatherill, G., Cotton, F., Pilz, M., Kwak, D. Y., Kawase, H. (2021): An open-source site database of strong-motion stations in Japan: K-NET and KiK-net (v1.0.0). - Earthquake Spectra, 37, 3, 2126-2149.
https://doi.org/10.1177/8755293020988028


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5005929
Abstract
This article describes an open-source site database for a total number of 1742 earthquake recording sites in the K-NET (Kyoshin network) and KiK-net (Kiban Kyoshin network) networks in Japan. This database contains site characterization parameters directly derived from available velocity profiles, including average wave velocities, bedrock depths, and velocity contrast. Meanwhile, it also consists of earthquake horizontal-to-vertical spectral ratio (HVSR) and peak parameters, for example, peak frequency, amplitude, width, and prominence. In addition, the site database also comprises topographic and geological proxies inferred from regional models or maps. Each parameter is derived in a consistent manner for all sites. This site database can benefit the application of machine learning techniques in studies on site amplification. Besides, it can facilitate, for instances, the search of the optimal site parameter(s) for the prediction of site amplification, the development and testing of ground-motion models or methodologies, as well as investigations on spatial or regional variability in site response. All resources (the site database, earthquake HVSR data at all sites, and the MATLAB script for peak identification) can be freely accessed via: https://doi.org/10.5880/GFZ.2.1.2020.006