Multivariate Statistical Analysis for Seismotectonic Provinces Using Earthquake, Active Fault, and Crustal Structure Datasets

Kikuchi, Takashi; Tsukada, Masataka; Fujita, Masatoshi

doi:10.1007/978-4-431-55822-4_2

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…Their results showed to what degree people were aware of the likelihood of danger and vulnerability in their area of residence. The whole of Japan was zoned in [14] using statistical methods and principal component analysis (PCA) based on gravity, earthquake, active fault and seismic parameters, and in [15] risk assessment using an artificial neural network (ANN) was performed, which addressed the lack of accurate validation methods which can be one of the shortcomings of these studies. Using social, environmental and physical metrics, another study performed post-earthquake hazard modeling and studied the health of individuals and the threat of poisonous insects, using a hierarchical analysis process model to weigh the criteria [16].…”

Section: Introductionmentioning

confidence: 99%

Earthquake Vulnerability Mapping Using Different Hybrid Models

et al. 2020

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The main purpose of the present study was to mathematically integrate different decision support systems to enhance the accuracy of seismic vulnerability mapping in Sanandaj City, Iran. An earthquake is considered to be a catastrophe that poses a serious threat to human infrastructures at different scales. Factors affecting seismic vulnerability were identified in three different dimensions; social, environmental, and physical. Our computer-based modeling approach was used to create hybrid training datasets via fuzzy-multiple criteria analysis (fuzzy-MCDA) and multiple criteria decision analysis-multi-criteria evaluation (MCDA-MCE) for training the multi-criteria evaluation–logistic regression (MCE–LR) and fuzzy-logistic regression (fuzzy-LR) hybrid model. The resulting dataset was validated using the seismic relative index (SRI) method and ten damaged spots from the study area, in which the MCDA-MCE model showed higher accuracy. The hybrid learning models of MCE-LR and fuzzy-LR were implemented using both resulting datasets for seismic vulnerability mapping. Finally, the resulting seismic vulnerability maps based on each model were validation using area under curve (AUC) and frequency ratio (FR). Based on the accuracy assessment results, the MCDA-MCE hybrid model (AUC = 0.85) showed higher accuracy than the fuzzy-MCDA model (AUC = 0.80), and the MCE-LR hybrid model (AUC = 0.90) resulted in more accurate vulnerability map than the fuzzy-LR hybrid model (AUC = 0.85). The results of the present study show that the accuracy of modeling and mapping seismic vulnerability in our case study area is directly related to the accuracy of the training dataset.

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Section: Introductionmentioning

confidence: 99%

Earthquake Vulnerability Mapping Using Different Hybrid Models

et al. 2020

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“…Nakajima et al (2009) provide an in-depth analysis of the Tokyo region, and provide important data on slab geometry. Otherwise, research on this topic has focused on the seismic potential of different domains (e.g., Triyoso and Shimazaki, 2012), with a multivariate statistical approach adopted by Kumamoto et al (2016) allowing a revision focused on moment magnitude. Ghimire and Kasahara (2009) focus on stress analysis, linking regional stress axes to P-axis orientation during earthquake moment release, but this analysis did not account for fault kinematics.…”

Section: Introductionmentioning

confidence: 99%

Lineaments and earthquake ruptures on the East Japan megathrust

et al. 2018

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In this paper we describe the earthquake geology of East Japan, based on a seismotectonic analysis of foreshocks and aftershocks for the 2011 Tohoku-oki Great Earthquake. The earthquake geology is defined by three compressional buttresses that are separated by channels dominated by extensional earthquakes. In the 2011 earthquake sequence, most activity occurred in the Tohoku-oki extensional channel. This is bounded by seismotectonic lineaments that run subparallel to the slip direction of thrust-fault earthquakes in the adjacent compressional buttresses, and to the slip direction of landward-dipping normal-fault aftershocks in the subducting Pacific plate. The northern bounding seismotectonic lineament of the Tohoku-oki extensional channel runs WNW-ESE ~15 km north of the Miyagi Volcanic Lineament. The southern bounding seismotectonic lineament runs ~20 km to the south of the Fukushima Volcanic Lineament. These lineaments may reflect faults that splay from deeper structures beneath the volcanic lineaments. In any case, the seismotectonic lineaments appear to reflect zones of weakness, and as is the case in any load-bearing architecture, precursor movements on such focusing structures may herald the onset of catastrophic failure. We discovered that two-thirds of all major earthquakes with moment magnitude M w ≥6.9 in the past 40 years in East Japan began within 15 km of the seaward prolongation of a volcanic lineament, and that motion across the northern seismotectonic lineament reversed its sense in the days prior to the 2011 Great Earthquake, suggesting the onset of yield. We infer that continuous geodetic monitoring across the East Japan lineaments might thus provide useful signals for future hazard assessment.

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“…Today, multivariate statistical analyses to study volcanic phenomena are more addressed to sectorial data (Hernández-Antonio et al 2015;Steinhorst et al 2001;Join et al 1997;Anazawa and Yoshida 1994;Velasco-Tapia 2014;Jamieson et al 2015;Buccianti et al 2015). A multivariate statistical approach applied to interdisciplinary datasets is only present in some works (Kumamoto et al 2016, Avery et al 2017, where it is shown how useful this methods can be for the seismic and volcanic risk assessment. Multidimensional analysis allows, in fact, to explore a subspace of the original variables space where independent phenomena can be more easily identified.…”

Section: Introductionmentioning

confidence: 99%

Multivariate approach to evaluate the relationship among geophysical and geochemical variables during an unrest period at Campi Flegrei caldera (Italy)

et al. 2018

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Campi Flegrei is a caldera in Southern Italy, which has manifested signs of significant unrest in the last years. Indeed, during volcanic crises, the ground of Campi Flegrei caldera begin to grow steadily, the earthquake swarms become more common and strong variations in the chemical composition of fumaroles are observed. In the Campi Flegrei volcanic area there is a spread ground deformation monitoring network. In the years 1983-1985 the bradiseism showed an increasing trend of ground uplift with a fairly fast velocity. In the following years the phenomenon tends to decrease: the earthquakes number is near to zero, the vertical ground displacement decreases, the fumaroles modify the gas emissions, the soil temperature decreases. The main object of this study is to evaluate, by means of variables comparison, in a counterclockwise periods, the relationship among geochemical data of fumaroles, earthquakes and ground deformations, to discover which variables can be considered signals (geochemical indicator) of the bradyseismic events during an unrest period.

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Multivariate Statistical Analysis for Seismotectonic Provinces Using Earthquake, Active Fault, and Crustal Structure Datasets

Cited by 7 publications

References 3 publications

Earthquake Vulnerability Mapping Using Different Hybrid Models

Earthquake Vulnerability Mapping Using Different Hybrid Models

Lineaments and earthquake ruptures on the East Japan megathrust

Multivariate approach to evaluate the relationship among geophysical and geochemical variables during an unrest period at Campi Flegrei caldera (Italy)

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