A study on the background and clustering seismicity in the Taiwan region by using point process models

被引:111
|
作者
Zhuang, JC
Chang, CP
Ogata, Y
Chen, YI
机构
[1] Inst Stat Math, Minato Ku, Tokyo 1068569, Japan
[2] Natl Cent Univ, Ctr Space & Remote Sensing Res, Jhongli, Taiwan
[3] Natl Cent Univ, Inst Stat, Chungli 320, Taiwan
关键词
D O I
10.1029/2004JB003157
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
[1] This paper investigates the shallow seismicity occurring in the Taiwan region during the 20th century using a stochastic declustering method that has been developed on the basis of the theory of the epidemic-type aftershock sequence model. It provides a probability based tool to objectively separate the space-time occurrences of earthquakes into a background and a clustering component. On the basis of the background and clustering seismicity rates, we discuss the correlation between the distribution of the cluster ratio and the regional seismotectonic structures. Specifically, we find that the areas of the highest clustering ratio correspond to the major strike-slip fault traces in and around Taiwan. Additionally, in the Taiwan inland region, during the period 1960 - 1990, the outputs for the stochastically declustered catalogue show a clear quiescence in background seismicity preceding the recovery of activation and the occurrences of the 1999 Chi-Chi earthquake of M(L)7.3, while the other active regions show stationary background activity. This could be interpreted as an effect of the aseismic slip in the Chi-Chi rupture fault, whereby the inland region around the Chi-Chi source becomes a stress shadow.
引用
收藏
页码:1 / 12
页数:15
相关论文
共 50 条
  • [1] Background seismicity in the central Apennines of italy: The Abruzzo region case study
    Bagh, S.
    Chiaraluce, L.
    De Gori, P.
    Moretti, M.
    Govoni, A.
    Chiarabba, C.
    Di Bartolomeo, P.
    Romanelli, M.
    TECTONOPHYSICS, 2007, 444 (1-4) : 80 - 92
  • [2] Using spatial point process models, clustering and space partitioning to reconfigure fire stations layout
    Bispo, Regina
    Vieira, Francisca G.
    Yokochi, Clara
    Marques, Filipe J.
    Espadinha-Cruz, Pedro
    Penha, Alexandre
    Grilo, Antonio
    INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, 2023,
  • [3] Measuring seismicity diversity and anomalies using point process models: case studies before and after the 2016 Kumamoto earthquakes in Kyushu, Japan
    Takao Kumazawa
    Yosihiko Ogata
    Hiroshi Tsuruoka
    Earth, Planets and Space, 69
  • [4] Measuring seismicity diversity and anomalies using point process models: case studies before and after the 2016 Kumamoto earthquakes in Kyushu, Japan
    Kumazawa, Takao
    Ogata, Yosihiko
    Tsuruoka, Hiroshi
    EARTH PLANETS AND SPACE, 2017, 69
  • [5] A study on seismicity in the Yunnan region by using the multidimensional stress release model
    Yin, Fengling
    Jiang, Changsheng
    Jia, Ke
    Han, Libo
    Zhang, Huai
    PHYSICS OF THE EARTH AND PLANETARY INTERIORS, 2019, 289 : 115 - 122
  • [6] Resource-Centric Process Mining: Clustering Using Local Process Models
    Delcoucq, Landelin
    Lecron, Fabian
    Fortemps, Philippe
    van der Aalst, Wil M. P.
    PROCEEDINGS OF THE 35TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING (SAC'20), 2020, : 45 - 52
  • [7] Using network models to approximate spatial point-process models
    Bauch, CT
    Galvani, AP
    MATHEMATICAL BIOSCIENCES, 2003, 184 (01) : 101 - 114
  • [8] Improving process models discovery using AXOR clustering algorithm
    Ariouat, Hanane
    Barkaoui, Kamel
    Akoka, Jacky
    Lecture Notes in Electrical Engineering, 2015, 339 : 623 - 629
  • [9] Maintainability Analysis of Equipment Using Point Process Models
    Barabadi, A.
    Garmabaki, A. H. S.
    Yuan, F.
    Lu, J.
    2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2015, : 797 - 801
  • [10] Operating point estimation for an absorption process using data clustering technique
    Majid, M. A. A., 1600, Asian Network for Scientific Information (13):