FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912153344> ?p ?o ?g. }

• W2912153344 endingPage "1140" @default.
• W2912153344 startingPage "1123" @default.
• W2912153344 abstract "Remote triggering of very low-frequency (VLF) earthquakes in the Nankai subduction zone by surface waves from a moderate to large, distant earthquake was examined using a Bayesian approach. The triggering of another type of tectonic slow earthquake/tremor and slow slip was previously discovered using simple signal processing techniques that exploit the different characteristic periods of the triggered and triggering event waveforms. Meanwhile, detecting low-amplitude VLF earthquakes embedded in high-amplitude seismic waves is challenging when they have similar characteristic periods, as established detection algorithms are inapplicable in such cases. Here we use a particle filter/smoother for time-series analysis combined with Markov chain Monte Carlo methods, to detect seismic signals and estimate the maximum likelihood source parameters of VLF events that might have been remotely triggered by surface waves from a moderate to large, distant earthquake, in data where the surface waves and target signals both have predominant periods between 10 and 100 s. This approach was applied to seismograms of the 2016 Mw 5.9 off-Kii Peninsula earthquake (Japan), recorded by the KiK-net borehole array in western Shikoku, Japan, where VLF events were previously reported. The borehole array is used because comparing surface and borehole records can identify vertically incident body waves based on depth-dependent phase differences, which do not appear in records of horizontally propagating surface waves. In particle filtering/smoothing, waveforms of a probable VLF event at each seismic station are predicted by a full-wavefield simulation in a 3-D structure model, and seismic interferometry that estimates traveltimes between surface and borehole sensors. A maximum-likelihood approach is used to estimate source parameters that best explain the surface observations predicted by the borehole observations and probable VLF signals. We found that six VLF events with magnitudes 3.4 ≤ Mw ≤ 4.3 likely occurred in the seismogenic regions of ambient low-frequency earthquakes/tremors (LFEs), and were likely triggered by the arrivals of high-amplitude surface waves. The triggering stress changes are estimated from 0.4 to 1.5 kPa, similar to the values for triggered LFEs reported previously. Since there were no triggered LFEs in western Shikoku following the 2016 Mw 5.9 earthquake, these VLF earthquakes are more sensitive to stress changes caused by surface waves from large earthquakes. This is the first reported example of dynamic triggering of VLF earthquakes." @default.
• W2912153344 created "2019-02-21" @default.
• W2912153344 creator A5086600660 @default.
• W2912153344 date "2019-02-05" @default.
• W2912153344 modified "2023-10-16" @default.
• W2912153344 title "Bayesian approach for detecting dynamically triggered very low-frequency earthquakes in the Nankai subduction zone and application to the 2016 <i>M</i>w 5.9 off-Kii Peninsula earthquake, Japan" @default.
• W2912153344 cites W1501586228 @default.
• W2912153344 cites W1515540741 @default.
• W2912153344 cites W1545050323 @default.
• W2912153344 cites W1561821466 @default.
• W2912153344 cites W1562218428 @default.
• W2912153344 cites W1666628699 @default.
• W2912153344 cites W1848602967 @default.
• W2912153344 cites W1973287273 @default.
• W2912153344 cites W1982103189 @default.
• W2912153344 cites W1985381416 @default.
• W2912153344 cites W1985982354 @default.
• W2912153344 cites W1989509352 @default.
• W2912153344 cites W2027778135 @default.
• W2912153344 cites W2052528966 @default.
• W2912153344 cites W2066714455 @default.
• W2912153344 cites W2070665913 @default.
• W2912153344 cites W2073593225 @default.
• W2912153344 cites W2075974107 @default.
• W2912153344 cites W2076952418 @default.
• W2912153344 cites W2092574457 @default.
• W2912153344 cites W2098839042 @default.
• W2912153344 cites W2124678555 @default.
• W2912153344 cites W2129722452 @default.
• W2912153344 cites W2142127434 @default.
• W2912153344 cites W2146993908 @default.
• W2912153344 cites W2165609874 @default.
• W2912153344 cites W2168634963 @default.
• W2912153344 cites W2200963127 @default.
• W2912153344 cites W2301497165 @default.
• W2912153344 cites W2463536963 @default.
• W2912153344 cites W2534816786 @default.
• W2912153344 cites W2626219529 @default.
• W2912153344 cites W2738226874 @default.
• W2912153344 cites W2756909408 @default.
• W2912153344 cites W2792795957 @default.
• W2912153344 cites W2792807186 @default.
• W2912153344 cites W2807262655 @default.
• W2912153344 cites W3121154744 @default.
• W2912153344 doi "https://doi.org/10.1093/gji/ggz073" @default.
• W2912153344 hasPublicationYear "2019" @default.
• W2912153344 type Work @default.
• W2912153344 sameAs 2912153344 @default.
• W2912153344 citedByCount "8" @default.
• W2912153344 countsByYear W29121533442019 @default.
• W2912153344 countsByYear W29121533442020 @default.
• W2912153344 countsByYear W29121533442021 @default.
• W2912153344 countsByYear W29121533442022 @default.
• W2912153344 countsByYear W29121533442023 @default.
• W2912153344 crossrefType "journal-article" @default.
• W2912153344 hasAuthorship W2912153344A5086600660 @default.
• W2912153344 hasBestOaLocation W29121533442 @default.
• W2912153344 hasConcept C121332964 @default.
• W2912153344 hasConcept C127313418 @default.
• W2912153344 hasConcept C150560799 @default.
• W2912153344 hasConcept C165205528 @default.
• W2912153344 hasConcept C165801399 @default.
• W2912153344 hasConcept C169744125 @default.
• W2912153344 hasConcept C172724772 @default.
• W2912153344 hasConcept C180205008 @default.
• W2912153344 hasConcept C187320778 @default.
• W2912153344 hasConcept C197424946 @default.
• W2912153344 hasConcept C38246216 @default.
• W2912153344 hasConcept C41008148 @default.
• W2912153344 hasConcept C58097730 @default.
• W2912153344 hasConcept C62520636 @default.
• W2912153344 hasConcept C76155785 @default.
• W2912153344 hasConcept C77928131 @default.
• W2912153344 hasConcept C8058405 @default.
• W2912153344 hasConcept C84174578 @default.
• W2912153344 hasConcept C90626213 @default.
• W2912153344 hasConceptScore W2912153344C121332964 @default.
• W2912153344 hasConceptScore W2912153344C127313418 @default.
• W2912153344 hasConceptScore W2912153344C150560799 @default.
• W2912153344 hasConceptScore W2912153344C165205528 @default.
• W2912153344 hasConceptScore W2912153344C165801399 @default.
• W2912153344 hasConceptScore W2912153344C169744125 @default.
• W2912153344 hasConceptScore W2912153344C172724772 @default.
• W2912153344 hasConceptScore W2912153344C180205008 @default.
• W2912153344 hasConceptScore W2912153344C187320778 @default.
• W2912153344 hasConceptScore W2912153344C197424946 @default.
• W2912153344 hasConceptScore W2912153344C38246216 @default.
• W2912153344 hasConceptScore W2912153344C41008148 @default.
• W2912153344 hasConceptScore W2912153344C58097730 @default.
• W2912153344 hasConceptScore W2912153344C62520636 @default.
• W2912153344 hasConceptScore W2912153344C76155785 @default.
• W2912153344 hasConceptScore W2912153344C77928131 @default.
• W2912153344 hasConceptScore W2912153344C8058405 @default.
• W2912153344 hasConceptScore W2912153344C84174578 @default.
• W2912153344 hasConceptScore W2912153344C90626213 @default.
• W2912153344 hasFunder F4320334764 @default.
• W2912153344 hasFunder F4320335136 @default.
• W2912153344 hasIssue "2" @default.

• next