Geology topics

Remy Bossu

Publications and source records attributed to Remy Bossu.

4 recordsLinked to original sources

USGS2024

The potential of crowdsourced data for the rapid impact assessment of large earthquakes: The 2023 M 7.8 Kahramanmaras‐Pazarcık, Turkiye, earthquake

Reliable and rapid impact assessment for large earthquakes is a challenge because it is difficult to rapidly determine the fault geometry and thus the spatial distribution of shaking intensities. In this retrospective study of the M 7.8 Kahramanmaraş‐Pazarcık, Türkiye, earthquake, we evaluate how eyewitness observations crowdsourced through the LastQuake system can improve such assessments. These data consist of felt reports describing the local level of shaking or damage and manually validated geolocated imagery. In the first part of this study, the methods used to derive macroseismic intensity values from felt reports, particularly for high values, are validated by comparison with independently determined intensities. This comparison confirms that the maximum intensity that can be derived from felt reports does not generally exceed VIII. A fatality estimate of 3000 could be made within a few hours by evaluating the number of people exposed to high intensities using the felt reports and assuming a point source. However, this estimate was known to be an underestimate because of the point‐source approximation; this underestimate was also confirmed by the geolocated imagery showing high levels of damage at epicentral distances well beyond those predicted by circular isoseismals. However, improved estimates could have been derived from the event’s ShakeMaps using the U.S. Geological Survey Prompt Assessment of Global Earthquakes for Response (PAGER) fatality loss‐modeling system, either by incorporating the felt reports into the ShakeMaps computation or using, in addition, a finite‐source (here line‐source) model derived from the felt reports using the Finite‐fault rupture Detector software. The inclusion of fault geometry would have resulted in a fatality estimate with data collected within 10 min of the origin determination, which was consistent with the final PAGER alert level and the reported death toll that were both only known days later. Although more work would be helpful to assess the reliability of the derived fault geometry, in regions where they are collected in large numbers, felt reports collected within 10 min of the earthquake can be used to substantially improve current fatality estimates.

Seismological Research Letters↗

USGS2021

When Punjab cried wolf: How a rumor triggered an “earthquake” in India

In recent years, earthquake felt reports contributed via online systems have provided increasingly valuable sources of data to characterize earthquakes and their effects. Contributed felt reports are accompanied by increases in website traffic, which are themselves potentially useful for the early detection of seismic events. In February 2017 the European‐Mediterranean Seismic Centre detected an unusual surge in traffic from the Punjab region in northwestern India, although no nearby seismic event was detected instrumentally. Had crowdsourcing detected a felt earthquake that instruments had missed? Or did Punjab cry wolf? In this Earthquake Lites report, we describe the sleuthing endeavor undertaken to find an answer.

Punjab↗

USGS2017

Toward a unified near-field intensity map of the 2015 Mw 7.8 Gorkha, Nepal, Earthquake

We develop a unified near-field shaking intensity map for the 25 April 2015 M w 7.8 Gorkha, Nepal, earthquake by synthesizing intensities derived from macroseismic effects that were determined by independent groups using a variety of approaches. Independent assessments by different groups are generally consistent, with minor differences that are likely due in large part to differences in spatial sampling. Throughout most of the near-field region, European Macroseismic Scale (EMS-98) intensities were generally close to 7 EMS. In the Kathmandu Valley, intensities were somewhat higher (6.5–7.5) along the periphery of the valley and in the adjacent foothills than in the central valley, where they were ≈6. The results are consistent with instrumental intensity values estimated from available data using a published relationship between peak ground acceleration (PGA) and intensity. Using this relationship to convert intensities to PGA, we estimate strong-motion PGA de-amplification factors of ≈0.7 in the central Kathmandu Valley, with amplification of ≈1.6 in adjacent foothills. The results support the conclusion that the Kathmandu Valley experienced a pervasively nonlinear response during the Gorkha main shock.

Earthquake Spectra↗

USGS2016

Thumbnail‐based questionnaires for the rapid and efficient collection of macroseismic data from global earthquakes

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.

Seismological Research Letters↗