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, including missed events in non-populated areas, poor earthquake locations, and a 10-percent false trigger rate. To leverage the strengths and mitigate the weaknesses of both the crowd-sourced and instrument-based seismic systems, the project team used the rapid tweet-based detections as seeds for seismic processing of event location, phase data association, and magnitude determination. The rapid crowd-source detections allow the seismic systems to focus in on a region of interest, thus reducing the number of instrumental observations necessary to process an event and, in turn, accelerate the processing.
To seamlessly integrate these crowd-sourced detections with numerous existing processing systems, the detections were converted to an internationally recognized format for seismic data exchange and were distributed via existing standard mechanisms. Algorithmic improvements were made to the core tweet-based system to provide improved locations to better support the integration of the data. After successful integration of the Twitter and seismic data, the project team integrated an additional type of crowd-sourced earthquake detections that are derived from analysis of Internet traffic and produced by the European-Mediterranean Seismological Centre (EMSC). These data, referred to as “flashsourcing,” further increase the spatial coverage of the crowd-sourced detections.
Principal Investigator : Michelle Guy, Paul S Earle
Cooperator/Partner : Jessica S Turner, Remy Bossu, Robert Steed
- Source: USGS Sciencebase (id: 56d874b1e4b015c306f6cfb8)
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, including missed events in non-populated areas, poor earthquake locations, and a 10-percent false trigger rate. To leverage the strengths and mitigate the weaknesses of both the crowd-sourced and instrument-based seismic systems, the project team used the rapid tweet-based detections as seeds for seismic processing of event location, phase data association, and magnitude determination. The rapid crowd-source detections allow the seismic systems to focus in on a region of interest, thus reducing the number of instrumental observations necessary to process an event and, in turn, accelerate the processing.
To seamlessly integrate these crowd-sourced detections with numerous existing processing systems, the detections were converted to an internationally recognized format for seismic data exchange and were distributed via existing standard mechanisms. Algorithmic improvements were made to the core tweet-based system to provide improved locations to better support the integration of the data. After successful integration of the Twitter and seismic data, the project team integrated an additional type of crowd-sourced earthquake detections that are derived from analysis of Internet traffic and produced by the European-Mediterranean Seismological Centre (EMSC). These data, referred to as “flashsourcing,” further increase the spatial coverage of the crowd-sourced detections.
Principal Investigator : Michelle Guy, Paul S Earle
Cooperator/Partner : Jessica S Turner, Remy Bossu, Robert Steed
- Source: USGS Sciencebase (id: 56d874b1e4b015c306f6cfb8)