Rapid earthquake response: The state-of-the art and recommendations with a focus on European systems

Guerin-Marthe, S.; Gehl, Pierre; Negulescu, Caterina; Auclair, Samuel; Fayjaloun, Rosemary

doi:10.1016/j.ijdrr.2020.101958

Cited by 29 publications

(19 citation statements)

References 42 publications

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“…This section examines the difference between traditional and alternative approaches to RELA and addresses some of the weaknesses of traditional loss assessment systems, which serve as a motivation for proposing the new approach. An overview of existing systems was given by Erdik et al (2011) and more recently by Guerin-Marthe et al (2021). According to the latter, rapid loss assessment systems provide near real-time ground motion, damage, and loss estimates.…”

Section: Related Work On Relamentioning

confidence: 99%

“…Guerin-Marthe et al (2021) provide an overview of the operational shake map systems with specific information about their name, location, institution, method, status, measured ground motions, and site amplification model. Also notable is their observation that, “the uncertainties originate from the ground motion model itself, and estimations of epicentral parameters (location, depth, and magnitude), the fault mechanism, and the map of soil classes” (Guerin-Marthe et al, 2021).…”

Section: Related Work On Relamentioning

confidence: 99%

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Rapid earthquake loss assessment based on machine learning and representative sampling

2021

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This article proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A random forest classification model predicts a damage probability distribution that, combined with an expert-defined repair cost matrix, enables the calculation of the expected repair costs for each building and, in aggregate, of direct losses in the earthquake-affected area. The proposed building representation does not include explicit information about the earthquake and the soil type. Instead, such information is implicitly contained in the spatial distribution of damage. To capture this distribution, a sampling algorithm, based on K-means clustering, is used to select a minimal number of buildings that represent the area of interest in terms of its seismic risk, independently of future earthquakes. To observe damage states in the representative set after an earthquake, the proposed framework utilizes a local network of trained damage assessors. The model is updated after each damage observation cycle, thus increasing the accuracy of the current loss assessment. The proposed framework is exemplified using the 2010 Kraljevo, Serbia earthquake dataset.

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Section: Related Work On Relamentioning

confidence: 99%

Section: Related Work On Relamentioning

confidence: 99%

Rapid earthquake loss assessment based on machine learning and representative sampling

2021

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“…They provide major spatial information, particularly in the first 50 km, with a ratio of up to a hundred between the number of communal intensities and instrumental measurements. As soon as earthquakes occur and for crisis management, the shakemaps deduced in particular from the preliminary intensities make it possible to rapidly model damage if one has knowledge of the vulnerability of buildings in the affected zones [Guérin-Marthe et al, 2021]. Beyond crisis management, the final intensities derived from the communal questionnaires and the field mission can be used to produce a reference shakemap for the event.…”

Section: Macroseismic Intensities Collected In France Frommentioning

confidence: 99%

1921–2021: 100 years of macroseismic studies at BCSF

Sira¹,

Cara²,

Schlupp³

et al. 2022

Comptes Rendus. Géoscience

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“…Other regional shakemaps for South-East of France are produced since 2015 (CASSAT project -10 to 20 shakemaps per year from 2015 to 2018) with integration of macroseismic data since 2018 (RISVAL project, sismoazur.oca.eu -several tens of shakemaps since the beginning of 2019). For more details, an in-depth comparison of these systems is presented by Guérin-Marthe et al (2020).…”

Section: Productsmentioning

confidence: 99%

The Transversal Seismicity Action RESIF: A Tool to Improve the Distribution of the French Seismicity Products

Masson

Auclair

Bertil

et al. 2021

Seismological Research Letters

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In recent years, the French seismological, geodetic, and gravimetric community has been structured within Réseau Sismologique et géodésique Français (RESIF) (French seismological and geodetic network). In addition to instrumental developments, RESIF has structured the work on French seismicity (metropolitan and overseas) within the RESIF transverse seismicity action (ATS). The purpose of this article is to present the ATS and the way it is structured to propose to the community different products: seismicity bulletin and catalog, historical and instrumental macroseismicity data, and ShakeMaps. The places where these products can be found are indicated, as well as the way they are realized and the improvements in progress for a better realization and availability. The link with European plate observing system is also underlined.

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Rapid earthquake response: The state-of-the art and recommendations with a focus on European systems

Cited by 29 publications

References 42 publications

Rapid earthquake loss assessment based on machine learning and representative sampling

Rapid earthquake loss assessment based on machine learning and representative sampling

1921–2021: 100 years of macroseismic studies at BCSF

The Transversal Seismicity Action RESIF: A Tool to Improve the Distribution of the French Seismicity Products

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