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Thumbnail‐Based Questionnaires for the Rapid and Efficient Collection of Macroseismic Data from Global Earthquakes

descriptionPublicationkeyboard_double_arrow_right Article 26 Oct 2016 Singapore Seismological Society of America (SSA)Seismological Research Letters, volume 88, pages 72-81 (issn: 0895-0695, eissn: 1938-2057,

Authors: Rémy Bossu; Matthieu Landès; Fréderic Roussel; Robert Steed; Gilles Mazet-Roux; Stacey S Martin; Susan E. Hough;

doi: 10.1785/0220160120

Thumbnail‐Based Questionnaires for the Rapid and Efficient Collection of Macroseismic Data from Global Earthquakes

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Abstract

The collection of earthquake testimonies (i.e., qualitative descriptions of felt shaking) is essential for macroseismic studies (i.e., studies gathering information on how strongly an earthquake was felt in different places), and when done rapidly and systematically, improves situational awareness and in turn can contribute to efficient emergency response. In this study, we present advances made in the collection of testimonies following earthquakes around the world using a thumbnail‐based questionnaire implemented on the European‐Mediterranean Seismological Centre (EMSC) smartphone app and its website compatible for mobile devices. In both instances, the questionnaire consists of a selection of thumbnails, each representing an intensity level of the European Macroseismic Scale 1998. We find that testimonies are collected faster, and in larger numbers, by way of thumbnail‐based questionnaires than by more traditional online questionnaires. Responses were received from all seismically active regions of our planet, suggesting that thumbnails overcome language barriers. We also observed that the app is not sufficient on its own, because the websites are the main source of testimonies when an earthquake strikes a region for the first time in a while; it is only for subsequent shocks that the app is widely used. Notably though, the speed of the collection of testimonies increases significantly when the app is used. We find that automated EMSC intensities as assigned by user‐specified thumbnails are, on average, well correlated with “Did You Feel It?” (DYFI) responses and with the three independently and manually derived macroseismic datasets, but there is a tendency for EMSC to be biased low with respect to DYFI at moderate and large intensities. We address this by proposing a simple adjustment that will be verified in future earthquakes. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Published version

Country

Singapore

Related Organizations

Nanyang Technological University
Singapore
AUS (United States)
United States
European-Mediterranean Seismological Centre
France

Subjects by Vocabulary

Microsoft Academic Graph classification: Information retrieval Situation awareness Computer science Thumbnail Computer-assisted web interviewing computer.software_genre Emergency response European Macroseismic Scale Smartphone app Data mining computer

Keywords

Macroseismic studies, Geophysics, Thumbnail‐Based Questionnaires

30 references, page 1 of 3

Ambraseys, N. N., and J. Douglas (2004). Magnitude calibration of north Indian earthquakes, Geophys. J. Int. 159, no. 1, 165-206.

Amorèse, D., R. Bossu, and G. Mazet-Roux (2015). Automatic clustering of macroseismic intensity data points from internet questionnaires: Efficiency of the partitioning around medoids (PAM), Seismol. Res. Lett. 86, no. 4, 1171-1177.

Boatwright, J., and E. Phillips (2012). Exploiting the demographics of “Did You Feel It?” responses to estimate the felt area of moderate earthquakes, Seismol. Res. Lett. 84, 149.

Bossu, R., S. Gilles, G. Mazet-Roux, and F. Roussel (2011). Citizen seismology: How to involve the public in earthquake response, in Comparative Emergency Management: Examining Global and Regional Responses to Disasters, CRC, Boca Raton, Florida, 237-260.

Bossu, R., S. Gilles, G. Mazet-Roux, F. Roussel, L. Frobert, and L. Kamb (2012). Flash sourcing, or rapid detection and characterization of earthquake effects through website traffic analysis, Ann. Geophys. 54, no. 6, 716-727, doi: 10.4401/ag-5265.

Bossu, R., M. Laurin, G. Mazet-Roux, F. Roussel, and R. Steed (2015). The importance of smartphones as public earthquake-information tools and tools for the rapid engagement with eyewitnesses: A case study of the 2015 Nepal earthquake sequence, Seismol. Res. Lett. 86, no. 6, 1587-1592.

Bossu, R., S. Lefebvre, Y. Cansi, and G. Mazet-Roux (2014). Characterization of the 2011 Mineral, Virginia, earthquake effects and epicenter from website traffic analysis, Seismol. Res. Lett. 85, no. 1, 91-97.

Bossu, R., G. Mazet-Roux, V. Douet, S. Rives, S. Marin, and M. Aupetit (2008). Internet users as seismic sensors for improved earthquake response, Eos Trans. AGU 89, no. 25, 225-226. [OpenAIRE]

Bossu, R., G. Mazet-Roux, F. Roussel, R. Steed, and C. Etivant (2015). The EMSC tools used to detect and diagnose the impact of global earthquakes from direct and indirect eyewitnesses' contributions, Information Systems for Crisis Response and Management (ISCRAM) 2015 Conference Proceedings, Kristiansand, Norway, 24-27 May 2015, http://iscram2015.uia.no/wp‑content/uploads/2015/05/8‑9.pdf (last accessed May 2016).

Bossu, R., R. Steed, G. Mazet-Roux, F. Roussel, and C. Etivant (2015). The key role of eyewitnesses in rapid impact assessment of global earthquakes, in Earthquakes and their Impact on Society, S. D'Amico (Editor), Springer Natural Hazards, Springer.

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	27
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average