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Crowd-Sourced Earthquake Detections Integrated into Seismic Processing


The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes worldwide using data solely mined from Twitter messages, known as “tweets.” The extensive spatial coverage and near instantaneous distribution of the tweets enable rapid detection of earthquakes often before seismic data are available in sparsely instrumented areas around the world. Although impressive for its speed, the tweet-based system has weaknesses, [...]


Principal Investigator :
Michelle Guy, Paul S Earle
Cooperator/Partner :
Jessica S Turner, Remy Bossu, Robert Steed
CMS Group :
Community for Data Integration - CDI

Attached Files

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“Distribution of time delays to detect a felt earthquake for Flashsourcing & TED ”
thumbnail 141.12 KB image/png
“Example of QuakeML”
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“CDI Monthly Meeting Presentation”
827.13 KB application/pdf


To leverage the strengths and mitigate the weaknesses of both the crowd-sourced and instrumentally-based systems, we will use the rapid twitter-based detections as seeds for our instrument-based seismic processing for event location, phase data association, and magnitude determination. The rapid crowd-source detections will allow the instrumental systems to focus in on a region of interest thus reducing the number of instrumental observations necessary to process an event and intern speeding up the processing. To seamlessly integrate these crowd-sourced detections with numerous existing processing systems, the detections will be converted to internationally recognized formats for seismic data exchange and be distributed via existing standard mechanisms.

Project Extension

productDescriptionPrevious related CDI funded project Previous PI correspondence: 505bb947e4b08c986b327ba5

Distribution of time delays to detect a felt earthquake for Flashsourcing & TED
Distribution of time delays to detect a felt earthquake for Flashsourcing & TED



  • Community for Data Integration (CDI)

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