Research ArticleGEOPHYSICS

Crowdsourcing triggers rapid, reliable earthquake locations

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Science Advances  03 Apr 2019:
Vol. 5, no. 4, eaau9824
DOI: 10.1126/sciadv.aau9824
  • Fig. 1 CsLoc fuses crowdsourced and seismic detection of earthquakes.

    Crowdsourced detections are quick but do not yield the physical properties of an event, and some detections are not related to seismic events. Seismic networks need strong quality criteria for the automatic publication of seismic events to avoid false detections. The fusion of the two sources of data improves the reliability of crowdsourced detections and reduces the response time of a seismic network for the rapid location of felt events.

  • Fig. 2 The CsLoc procedure.

    (A) Flowchart of the CsLoc association and location process. (B) First iteration of a typical CsLoc analysis. Fast-arriving Pn-phases up to 10° from the initial crowdsourced location are considered in the association process. (C) Phases within three times the median absolute deviation (MAD) are used for the iLoc location analysis. (D and E) The location process typically obtains a stable solution in less than 10 iterations. By the 10th iteration, more phases have arrived and the arrival times are highly aligned on the predicted Pn travel-time curve. Consequently, many more stations contribute to the location (note that the EMSC-published epicenter is hidden by the CsLoc epicenter).

  • Fig. 3 Testing of CsLoc on crowdsourced detections from 2016 and 2017.

    (A) Results of CsLoc analyses overlaid on a density plot of the number of GEOFON seismic stations within 1000 km of each position. Successful locations are related to local network density: Almost all nonlocalized events are out of the network. (B) Results broken down by crowdsourced detection source. Note that some earthquakes were detected by multiple systems. Success rates are similar for each source of event detection. (C) Histogram of separation of first publishable CsLoc result for each earthquake with respect to the final EMSC-published epicenter.

  • Fig. 4 Latency of CsLoc during testing.

    (A) Breakdown of the analysis delays for the 735 earthquakes located by CsLoc using the earliest publishable location. Analysis is largely limited by the time required to collect sufficient phases. (B) Violin plot of the minimum publication delays for CsLoc, GEOFON, and EMSC from an analysis of the set of 429 earthquakes detected by both CsLoc and GEOFON within 10 min of the origin time.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/4/eaau9824/DC1

    Fig. S1. Analysis of the crowdsourced detections during 2016–2017 that could be associated with EMSC-published epicenters, considering each detection method individually.

    Fig. S2. A Venn diagram of the earthquakes detected by each crowdsourced system during 2016–2017.

    Fig. S3. Scatter graphs showing all obtained locations for the 10th iteration of the CsLoc analyses for all 2200 detections that were associated with an EMSC epicenter.

    Fig. S4. Summary of the test dataset and its results starting from the 2590 crowdsourced detections; the transition from “seismic” to “distinct earthquakes” corresponds to the deduplication of detections from the multiple crowdsourced detection methods.

    Fig. S5. An analysis of the 735 earthquakes located by CsLoc with respect to earthquake magnitude.

    Fig. S6. The earthquakes located by CsLoc and GEOFON by earthquake magnitude; CsLoc had a wider spectrum of magnitudes, locating a larger number of events of magnitude lower than M5 with respect to GEOFON in the first 10 min.

    Table S1. Summary statistics for crowdsourced detections at the EMSC during 2016–2017.

    Table S2. Summary statistics for the earthquakes detected by each crowdsourced detection.

    Table S3. Summary of the 735 earthquakes located by CsLoc that met the publication criteria.

    Table S4. Statistics for the 429 earthquakes located by both GEOFON and CsLoc within 10 min of the origin time.

  • Supplementary Materials

    This PDF file includes:

    • Fig. S1. Analysis of the crowdsourced detections during 2016–2017 that could be associated with EMSC-published epicenters, considering each detection method individually.
    • Fig. S2. A Venn diagram of the earthquakes detected by each crowdsourced system during 2016–2017.
    • Fig. S3. Scatter graphs showing all obtained locations for the 10th iteration of the CsLoc analyses for all 2200 detections that were associated with an EMSC epicenter.
    • Fig. S4. Summary of the test dataset and its results starting from the 2590 crowdsourced detections; the transition from “seismic” to “distinct earthquakes” corresponds to the deduplication of detections from the multiple crowdsourced detection methods.
    • Fig. S5. An analysis of the 735 earthquakes located by CsLoc with respect to earthquake magnitude.
    • Fig. S6. The earthquakes located by CsLoc and GEOFON by earthquake magnitude; CsLoc had a wider spectrum of magnitudes, locating a larger number of events of magnitude lower than M5 with respect to GEOFON in the first 10 min.
    • Table S1. Summary statistics for crowdsourced detections at the EMSC during 2016–2017.
    • Table S2. Summary statistics for the earthquakes detected by each crowdsourced detection.
    • Table S3. Summary of the 735 earthquakes located by CsLoc that met the publication criteria.
    • Table S4. Statistics for the 429 earthquakes located by both GEOFON and CsLoc within 10 min of the origin time.

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