2006 Fiscal Year Final Research Report Summary
RESEARCH TOWARDS REAL SEISMIC ACTIVITY MONITORING SYSTEM BASED ON STATISTICAL MODELING
| Project/Area Number |
17540395
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Solid earth and planetary physics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
SHIMAZAKI Kunihiko The University of Tokyo, Earthquake Research Institute, Professor (50012951)
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| Project Period (FY) |
2005 – 2006
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| Keywords | Seismic activity / Earthquake forecasting / Anomaly detection / Monitoring system |
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| Research Abstract |
No real earthquake monitoring system is available, although various researches have been reported on anomalous seismic activity prior to a large earthquake. This study consists of three parts: 1) detection system of anomalies, 2) prior earthquake probability estimate, and 3) presentation system of results. The first of all, a monitoring system of seismic activity is constructed to detect anomalous seismicity. The most prominent feature of seismic activity is concentration in space and time, which is best described by the ETAS model proposed by Ogata in 1998. According to the model, all the activity can be divided into two: statistically independent background activity and statistically dependent aftershocks. Most of the previous analysis often avoided to separate the two objectively, thus judged ordinary activity as unusual, or could not detect anomaly prior to a large earthquake. We used background seismicity to detect unusual activity after stochastically separating independent and d
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ependent evens using the intensity function. We compare the results obtained by applying the detection system to the real seismicity data and also to synthetic seismicity data produced from the ETAS model. We use the difference in AIC (=SAIC) between two models: one assuming anomalous activity during a certain time-period and the other assuming normal activity throughout all the time period. Our analysis shows seismic quiescence showing SAIC smaller than -8 and high seismicity showing SAIC larger than 10 are significant anomalies. For the second subject, we constructed eight time-invariant probabilistic models of earthquake potential on the basis of various proposals made in the past. Then we test them against historical earthquake data and concluded that the spatially smoothed synthesized seismicity model based on active fault data is the most reliable. Thirdly we recommend to use animation movie to show the result of earthquake monitoring. As an example, the spatial distribution of b-value is shown to change in time in our report. Less
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Research Products
(2 results)
