Web-based macroseismic survey in Italy: method validation and results

Sbarra, Paola; Tosi, Patrizia; Rubeis, Valerio De

doi:10.1007/s11069-009-9488-7

Cited by 54 publications

(28 citation statements)

References 8 publications

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“…This microseismic survey (by analogy with macroseismic surveys) was similar to the "Did You Feel It?" form of most seismological surveys (Atkinson and Wald, 2007;Sbarra et al, 2010;Wald et al, 2012). We used the iconographic representation originally proposed by the French Central Bureau for Seismology (BCSF) of Strasbourg University and shown on the SismoCom mobile tool for how the quake was felt (Sira et al, 2010).…”

Section: Observation Of the Coupling In Grenoblementioning

confidence: 99%

Experimental and Numerical Evidence of the Clustering Effect of Structures on Their Response during an Earthquake: A Case Study of Three Identical Towers in the City of Grenoble, France

Guéguen¹,

Colombi²

2016

Bulletin of the Seismological Society of America

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In this article, interpretation of an equivalent to a macroseismic intensity survey, performed in three identical stand-alone buildings located in Grenoble, France, after an M L 4.1 earthquake, reveals a clustering effect, resulting in different levels of perception of seismic loading by inhabitants. The clustering effect is confirmed using numerical simulation; the variation of the seismic response of the building in the middle of the cluster depends on the azimuth of the seismic source relative to the building cluster. The major effect is the splitting of its resonance frequency, accompanied by a decrease in vibration amplitude. We conclude that clustering has an impact on urban effects, calling into question the validity of seismic design, which considers buildings in urban areas as stand-alone constructions, and the interpretation of macroseismic intensity surveys conducted in dense urban areas.

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Section: Observation Of the Coupling In Grenoblementioning

confidence: 99%

Experimental and Numerical Evidence of the Clustering Effect of Structures on Their Response during an Earthquake: A Case Study of Three Identical Towers in the City of Grenoble, France

Guéguen¹,

Colombi²

2016

Bulletin of the Seismological Society of America

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“…The observed intensities were taken from three intensity databases, namely "Hai sentito il terremoto?" (HSIT; Sbarra et al, 2010), "Did You Feel It?" (DYFI; Wald, Quitoriano, Dengler, et al, 1999), and Database Macrosismico Italiano 2011 (DBMI11).…”

Section: Data the Databasesmentioning

confidence: 99%

Validating Intensity Prediction Equations for Italy by Observations

Mak¹,

Clements²,

Schorlemmer³

2015

Bulletin of the Seismological Society of America

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The engineering seismology community has recently recognized the importance of validating the performance of predictive models for seismic hazard by independent observations, yielding a number of studies on the relative performance of ground-motion prediction equations. The validation of intensity prediction equations (IPEs) has attracted less attention. We fill this gap by validating eight Italian IPEs plus one global IPE using five sets of Italian macroseismic intensity data, of which three are prospective and two retrospective to the models. We implemented multiple scoring methods to validate the models and found that the simple score of mean absolute error is sufficient to measure the general model performance. Good models consistently perform well under multiple methods and datasets, showing robustness. Models with physical functional forms are found to perform better. The global IPE performed well for Italian data, implying insignificant regional differences for IPEs. This result encourages grouping intensity data collected from multiple geographic regions, both from the Internet and traditional surveys, into a larger dataset for the use of future model development and validation.

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“…system, hereafter referred to as DYFI, Wald et al, 1999Wald et al, , 2011; and the "Hai Sentito il Terremoto?" system, Sbarra et al, 2010). The availability of Internet-based macroseismic intensity data (hereafter referred to as "iIntensity") is likely affected by the self-selection bias because responses are mostly voluntary.…”

Section: Introductionmentioning

confidence: 99%

What Makes People Respond to “Did You Feel It?”?

Mak

Schorlemmer

2016

Seismological Research Letters

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The data compilation of "Did You Feel It?" (DYFI) and other similar Internet-based macroseismic intensity databases relies on the voluntary responses from Internet users. A region of no responses could mean no perceivable ground shakings or no volunteers submitting responses. We examined the earthquake and socioeconomic conditions that affected the number of DYFI responses received for a region. A resulting statistical model described the expected number of DYFI responses received for an earthquake. We also showed that residents in California and the central and eastern United States followed similar behavior in responding to DYFI, despite the vast difference in seismicity for the two regions. This study allows for a quantitative definition of completeness for DYFI data. The presented modeling technique is applicable to other Internetbased macroseismic intensity databases.

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Web-based macroseismic survey in Italy: method validation and results

Cited by 54 publications

References 8 publications

Experimental and Numerical Evidence of the Clustering Effect of Structures on Their Response during an Earthquake: A Case Study of Three Identical Towers in the City of Grenoble, France

Experimental and Numerical Evidence of the Clustering Effect of Structures on Their Response during an Earthquake: A Case Study of Three Identical Towers in the City of Grenoble, France

Validating Intensity Prediction Equations for Italy by Observations

What Makes People Respond to “Did You Feel It?”?

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