English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Utilization of crowdsourced macroseismic observations to distinguish “high-impact” from “low-impact” earthquakes globally within minutes of an event

Authors

Lilienkamp,  Henning
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Bossu,  Rémy
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/fcotton

Cotton,  Fabrice
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Finazzi,  Francesco
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/gweather

Weatherill,  Graeme
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/svs

von Specht,  S.
0 Pre-GFZ, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in GFZpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Lilienkamp, H., Bossu, R., Cotton, F., Finazzi, F., Weatherill, G., von Specht, S. (2023): Utilization of crowdsourced macroseismic observations to distinguish “high-impact” from “low-impact” earthquakes globally within minutes of an event, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4118


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021557
Abstract
Rapid assessment of an earthquake’s impact on the affected society is a crucial first step of disaster management, determining further emergency measures. We demonstrate that macroseismic observations, collected as felt reports via the LastQuake service of the European Mediterranean Seismological Center, can be utilized to estimate the probability of a felt earthquake to have a “high impact” rather than a “low impact” on the affected population on a global scale. In our fully data-driven, transparent, and reproducible approach we compare the distribution of felt reports to documented earthquake impact in terms of economic losses, number of fatalities, and number of damaged or destroyed buildings. Using the distribution of felt-reports as predictive parameters and an impact measure as the target parameter, we infer a probabilistic model utilizing Bayes’ theorem and Kernel Density Estimation, that provides the probability of an earthquake to be “high impact”. For 393 felt events in 2021, a sufficient number of felt reports to run the model is collected within 10 minutes after the earthquake. While a clean separation of “high-impact” and “low-impact” events remains a challenging task, unambiguous identification of many “low-impact” events in our dataset is identified as a key strength of our approach. We consider our method a complementary and inexpensive impact assessment tools, that can be utilized instantly in all populated areas on the planet, with the necessary technological infrastructure. Being fully independent of seismic data, our framework poses an affordable option to support disaster management in regions that currently lack expensive seismic instrumentation.