Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets

Takashi Kumamoto, Masataka Tsukada, Masatoshi Fujita

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Seismotectonic zonation for seismic hazard assessment of background faults and earthquakes by the Headquarters for Earthquake Research Promotion (HERP [1]) is based on the results of the seismotectonic boundaries of Kakimi et al. [2]. However, several unsolved problems, such as map scale, remain in this approach for better prediction of the magnitude and frequency of blind earthquakes. The aim of this study was to construct a new quantitative and objective seismotectonic province map for the main islands of Japan (Honshu) for rational earthquake size estimation of blind faults and earthquakes. The resolution of the map was set as the second-order map grid of ca. 10 by 10 km of the Geographic Survey of Japan. Then, the parameters of (1) observed seismicity, (2) distribution of active faults converted to earthquake moment release rate, (3) width of the seismogenic layer, and (4) Bouguer gravity anomaly were assigned independently to each grid for principal component analysis. The first principal component of the principal analysis in this study represents the degree of tectonic activity for both the northeastern and southwestern Honshu islands. The resulting principal component scores were then applied to a cluster analysis to conduct quantitative classifications, and the result provided three and nine seismotectonic provinces in the northeastern and southwestern Honshu islands, respectively.

Original languageEnglish
Title of host publicationEarthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident
PublisherSpringer Japan
Pages31-41
Number of pages11
ISBN (Print)9784431558224, 9784431558200
DOIs
Publication statusPublished - Jan 1 2016

Fingerprint

Multivariate Statistical Analysis
seismotectonics
crustal structure
active fault
Earthquake
Earthquakes
Statistical methods
statistical analysis
Fault
earthquake
Principal Components
Japan
Grid
Cluster analysis
Cluster Analysis
Tectonics
hazard assessment
gravity anomaly
seismic hazard
Hazard

Keywords

  • Cluster analysis
  • Principal component analysis
  • Seismotectonic province map

ASJC Scopus subject areas

  • Engineering(all)
  • Environmental Science(all)
  • Earth and Planetary Sciences(all)
  • Mathematics(all)

Cite this

Kumamoto, T., Tsukada, M., & Fujita, M. (2016). Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets. In Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident (pp. 31-41). Springer Japan. https://doi.org/10.1007/978-4-431-55822-4_2

Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets. / Kumamoto, Takashi; Tsukada, Masataka; Fujita, Masatoshi.

Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident. Springer Japan, 2016. p. 31-41.

Research output: Chapter in Book/Report/Conference proceedingChapter

Kumamoto, T, Tsukada, M & Fujita, M 2016, Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets. in Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident. Springer Japan, pp. 31-41. https://doi.org/10.1007/978-4-431-55822-4_2
Kumamoto T, Tsukada M, Fujita M. Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets. In Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident. Springer Japan. 2016. p. 31-41 https://doi.org/10.1007/978-4-431-55822-4_2
Kumamoto, Takashi ; Tsukada, Masataka ; Fujita, Masatoshi. / Multivariate statistical analysis for seismotectonic provinces using earthquake, active fault, and crustal structure datasets. Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident. Springer Japan, 2016. pp. 31-41
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