USGS Open Innovation Earthquake Projects

Did You Feel It? (DYFI)

• Project Leads:
  • David Wald - USGS National Earthquake Information Center (NEIC)
  • Vince Quitoriano - 

• Tool / Instrument / Data:
  • DYFI Felt Report Online Questionnaire
  • DYFI Summary Maps Webpage
  • DYFI Annual Data Viewer

• Description:

  • Did You Feel It? (DYFI) collects information from people who felt an earthquake and creates maps that show what people experienced and the extent of damage.

  • DYFI Scientific Background
  • DYFI FAQs
  • DYFI Disclaimers
  • CitizenScience.gov Case Study - Did You Feel It?
  • CitizenScience.gov Catalog - Did You Feel It?
  • Crowd and Cloud - Did You Feel It?

• Purpose:
  • Detect earthquakes by mining Twitter data
  • Use the Twitter platform to rapidly share earthquake alerts to the public for free

• Publications:
  • DYFI Factsheet (Online Version | PDF Version}
  • USGS DYFI Comparison Poster

  • Atkinson, G.M., and Wald, D.J. (2007). “Did You Feel It?” Intensity Data: A Surprisingly Good Measure of Earthquake Ground Motion. Seismological Research Letters, 78: 362-368. https://doi.org/10.1785/gssrl.78.3.362.

  • Wald, D. J., and Dewey, J.W. (2005). Did You Feel It? Citizens Contribute to Earthquake Science. USGS Fact Sheet 2005-3016. https://doi.org/10.3133/fs20053016.

  • Wald, D.J., Quitoriano, V., Dengler, L.A., and Dewey J.W. (1999). Utilization of the Internet for Rapid Community Intensity Maps. Seismological Research Letters, 70(6): 680-697. https://doi.org/10.1785/gssrl.70.6.680.

  • Wald, D.J., Quitoriano, V., Worden, C.B., Hopper, M., and Dewey, J.W. (2012). USGS “Did You Feel It?” Internet-based Macroseismic Intensity Maps. Annals of Geophysics, 54(6). https://doi.org/10.4401/ag-5354.

• Related Projects:
  • DYFI Mobile App - Hack for Good Mobile Hackathon

Tweet Earthquake Dispatch (TED)

• Project Leads:
  • Paul Earle - USGS National Earthquake Information Center (NEIC)
  • Michelle Guy - USGS National Earthquake Information Center (NEIC)

• Tool / Instrument:

  • Tweet Earthquake Dispatch (TED)

  • TED Software

• Description:
  • TED Case Study on CitizenScience.gov
  • CitizenScience.gov Catalog - Tweet Earthquake Dispatch

  • TED harvests real-time tweets through a continuous connection to Twitter. The system applies a query parameter to reduce the stream to tweets that contain the keyword earthquake in several languages. The system also applies other data-cleaning techniques. It merges tweets, ordering them, accounting for duplicates and filling any data gaps. Data from aggregators — users who redistribute secondhand earthquake information — are removed from the dataset. For each tweet filtered by keyword, TED archives the creation time and text, the Twitter user location, the Twitter tweet ID, and the time the tweet appeared in the TED database. The system also uses the Yahoo Maps API Geocoding Service to estimate the latitude and longitude of the sender’s location, if provided. Around the clock, TED also ingests seismically derived earthquake information from the USGS’s near-real-time internal global earthquake stream. TED archives the earthquake time, region, magnitude and hypocenter (latitude, longitude and depth). It also records the source of the scientifically derived earthquake information. For earthquakes that have been verified using seismic instruments, TED subsequently sends out a tweet to followers with basic information about the earthquake.

  • @USGSted (USGS Twitter Earthquake Dispatch) distributes Twitter alerts for earthquakes worldwide with magnitudes of 5.5 and above. When citizens feel shaking activity, they often use the popular social media application, Twitter, to "tweet" what they are experiencing. The @USGSted application, in general terms, searches for tweets that contain the word "earthquake" or certain related terms and stores these messages to a database. From this database, scientists at the National Earthquake Information Center (NEIC) can then produce maps of locations and discern how severe an earthquake event might be as soon as tweets are received. In today's electronic-device society, tweets are received almost instantly after an earthquake begins.

  • Twitter provides a Java-level interface (twitter4j) to allow applications to request a set of tweets. Using this interface, a Java developer wrote code that accesses the Twitter stream, requests tweets that contain a keyword (for example, "earthquake"), and stores that data in a database. Because earthquakes are a global natural event, the keywords include international terms like "temblor" and "terremoto."

  • Anyone can track the updates from @USGSted. Follow the USGS tweets on significant earthquake activity (or add your own during an event!) by logging into Twitter.com and searching for “@USGSted.” Or, go directly to https://twitter.com/USGSted and set up an account.

  • Design Features

    • Extrapolating Geospatial Information: One of the advantages for the science community of retrieving data from Twitter is that each tweet contains a geospatial string of where the tweet came from. For the application design, we used Yahoo PlaceFinder to decode the location string from Twitter to a latitude and longitude. For the scientist, this latitude-longitude data can be plotted on a map to visualize the areas of impact.
    • Managing Peak Thresholds: When a major event occurs, there could be 40–50 tweets per second. This is a high level of data coming in for a short period of time. At these peak event times, the system must focus on storing the incoming tweets. We designed @USGSted so that if the incoming data load is higher than a specified threshold, the decoding of locations into lat/long values is deferred. These values are filled at a later time when the incoming tweet rate is below the threshold.
    • Compensating for Down Time: There are occasions when the Twitter interface is unavailable to the @USGSted application. Since the data is important for the scientific analysis, we created a separate process as part of the @USGSted solution that determines the last tweet received by the system and the current tweet ID issued by Twitter. If there is a discrepancy, this process attempts to recover tweets lost in the interim. By filling in any gaps, the application can provide a more consistent and complete dataset to the scientist.

• Purpose:

  • The main advantage of mining citizen reports through Twitter is speed.  Rapid tweet-based earthquake detection can potentially fill the gap between the time when an earthquake occurs and the time when seismically derived information becomes available.

  • TED detects two to three earthquakes a day, on average. Especially in regions with few seismometers, TED reports often come in before traditional seismic networks detect an earthquake, giving seismologists early warning. TED sometimes detects earthquakes entirely missed by USGS’s automatic processing system, thereby increasing the number of felt events known to the agency. In addition, the tweet text and attached images sometimes offer a rapid qualitative assessment of an earthquake’s impact.

• Publications:

  • Earle, P.S., Bowden, D.C., and Guy, M. (2012). Twitter Earthquake Detection: Earthquake Monitoring in a Social World. Annals of Geophysics, [S.l.], 54(6). http://dx.doi.org/10.4401/ag-5364.

  • Earle, P.S., Guy, M., Buckmaster, R., Ostrum, C., Horvath, S., and Vaughan, A. (2010). OMG Earthquake! Can Twitter Improve Earthquake Response? Seismological Research Letters, 81(2): 246-251. https://doi.org/10.1785/gssrl.81.2.246.

NetQuakes

• Project Leads:

• Tool / Instrument / Data:
  • NetQuakes
  • NetQuakes Data

• Description:

  • The USGS is working to achieve a denser and more uniform spacing of seismographs in select urban areas to provide better measurements of ground motion during earthquakes. These measurements improve our ability to make rapid post-earthquake assessments of expected damage and contribute to the continuing development of engineering standards for construction.

    To accomplish this, we developed a new type of digital seismograph that connects to a local network via WiFi and uses existing broadband connections to transmit data to USGS after an earthquake. The instruments are designed to be installed in private homes, businesses, public buildings and schools with an existing broadband connection to the internet. Data from these instruments is transmitted to USGS after an earthquake, and can be viewed here.

  • NetQuakes FAQs
  • CitizenScience.gov Catalog - NetQuakes

• Purpose:

  • Detect earthquakes

  • Increase seismic monitoring network by increasing density of seismographs in urban areas

• Publications:

Bridging Local Outreach & Seismic Signal Monitoring (BLOSSM)

• Project Lead:
  • Jefferson Chang - USGS Hawaiian Volcano Observatory (HVO)

• Description: 

  • Hawai‘i Island is home to Mauna Loa and Kīlauea, respectively the largest and most active volcanoes on the planet. The USGS Hawaiian Volcano Observatory (HVO) monitors, investigates, and assesses the hazards posed by these volcanoes since 1912. HVO uses real-time information from instruments to monitor thermal and visual changes, volcanic gas emissions, ground deformation, and seismic activity. However, most of these monitoring instruments are located along volcanic edifices and rift zones, far from heavily populated areas, such as Hilo, Kona, and Pāhoa. Increasing the coverage of monitoring stations on the island is financially impractical, due to the high cost of instrumentation. In recent years, publicly available data and technological advancements have given new momentum to citizen science initiatives. Data gathered by specialized instrumentation are reproducible by enthusiastic hobbyists, using readily available off-the-shelf components. We use emerging technology, such as the Raspberry Shake seismograph, to empower youth in a problem-based learning approach during a summer-long course. With guidance from HVO scientists, students essentially adopt the hazards mission of the USGS. Students not only aid in the volcano monitoring efforts on Hawai‘i Island, but also (1) take ownership of their own learning, (2) increase their capacity in STEM, and (3) engage the local community and address its needs.

• Purpose:
  • Increase density of seismic monitoring network coverage to detect earthquakes
  • Promote geoscience education of earthquake risk in K-12 schools and public learning spaces
  • Foster scientific literacy of earthquake risk to promote hazard awareness and mitigation
  • Develop a community of citizen seismologists to cultivate informed discussions
  • Make seismic data more accessible
  • Engage youth and underserved communities such as tribal or indigenous communities 

• Tool / Instrument:
  • Raspberry Shake
  • Raspberry Shake Products

• Publications / Presentations:
  • "Using Volcanic Hazards in Hawai‘i as a STEM Platform in Problem-Based Learning" Ignite OI Forum on March 16, 2020
  • Raspberry Shake Scientific Posters

Other Open Innovation Earthquake Projects

MyShake

• Project Leads:
  • Richard Allen - Director of Berkeley Seismology Lab, Professor in Department of Earth and Planetary Science at University of California, Berkeley

• Tool / Instrument:
  • MyShake Apple App Store
  • MyShake Google Play Store

• Description:
  • MyShake is the citizen science project bringing users together to build a global earthquake early warning network. Our app keeps you informed about earthquakes and monitors for them using data from your phone’s sensors. Our goal is to build a worldwide earthquake early warning network so that communities can reduce the impact of earthquakes. Since MyShake uses smartphones as earthquake sensors, it can be used everywhere - even in countries without access to traditional seismic technology.
  • MyShake collects motion data from your phone’s sensors and uses a patented neural network to determine whether that motion fits the model of an earthquake. When your phone is stationary, MyShake is ready to collect data from its motion sensors. MyShake uses a neural network to decide which motion is produced by earthquakes and which isn’t. When MyShake detects an earthquake, its network of phones records the shaking to collect valuable data.
  • MyShake Website
  • MyShake FAQs
  • Get the MyShake Earthquake Early Warning App! YouTube Video
  • MyShake Tutorial YouTube Video
  • Artificial Neural Networks and Seismology with MyShake YouTube Video

• Purpose:

  • MyShake delivers ShakeAlert™ across California: Earthquake alerts provided in partnership with USGS ShakeAlert™ and CalOES.

  • Quickly understand the impact of an earthquake: See damage and shaking reports submitted by other community members along with information from the USGS and other global earthquake authorities.

  • Share your experience: Felt an earthquake? Share your experience with fellow users and MyShake scientists.

  • Become a citizen scientist: Your device becomes an earthquake sensor and joins a smartphone network collecting valuable data.

  • Stay Informed: Get notifications about nearby earthquakes and track earthquakes around the globe.

• Publications:
  • Rochford, K., J. Strauss, Q. Kong, R.M. Allen (2018). MyShake: Using human-centered design methods to promote engagement in a smartphone-based global seismic network. Front. Earth Sci., doi: 10.3389/feart.2018.00237
  • Kong, Q., A. Inbal, R.M. Allen, Q. Lv, A. Puder (2018). Machine Learning Aspects of the MyShake Global Smartphone Seismic Network. Seismo. Res. Lett. , doi: 10.1785/0220180309
  • Kong, Q., R. M. Allen, M.D. Kohler, T.H. Heaton and J. Bunn (2018), Structural health monitoring of buildings using smartphone sensors, Seismo. Res. Lett., 89, 594-602, doi: 10.1785/0220170111
  • Kong, Q., R. M. Allen, and L. Schreier (2017), MyShake: Building a global smartphone seismic network, Geostrata, 44-53, July/August 2017
  • Kong, Q,. R. M. Allen, L. Schreier, (2016), MyShake: Initial Observations from a Global Smartphone Seismic Network, Geophys. Res. Lett., 106, 9369-10, doi: 10.1002/2016GL070955
  • Kong, Q,. R. M. Allen, L. Schreier, Y.-W. Kwon (2016), MyShake: A smartphone seismic network for earthquake early warning and beyond, Sci. Adv., 2, doi: 10.1126/sciadv.1501055
  • Allen, R.M., Kong, Q. & Martin-Short, R. (2019), The MyShake Platform: A Global Vision for Earthquake Early Warning, Pure Appl. Geophys., doi: 10.1007/s00024-019-02337-7

Quake-Catcher Network (QCN)

• Project Leads:
  • Elizabeth Cochran

• Tool / Instrument / Data:
  • Quake-Catcher Network
  • QCN Sensors
  • QCN Data
  • QCN Map

• Description:

  • Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can build community among schools, museums, and other learning environments to improve earthquake science awareness. The QCN is a seismic education network that utilizes strong-motion accelerometers to record nearby earthquake activity. As of June 2016, QCN is operated by the Southern California Earthquake Center (SCEC) and the Incorporated Research Institutions for Seismology (IRIS).

  • The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC). The volunteer computers monitor motion with vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever new strong motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes and which ones represent cultural noise (like doors slamming or trucks driving by).

  • CitizenScience.gov Catalog - Quake Catcher Network
  • Crowd and Cloud - Quake Catcher

• Purpose:

  • Detect earthquakes

  • Increase seismic monitoring network by increasing density of seismographs in urban areas
  • Educational learning

• Publications:

  • Cochran, E.S., Lawrence, J.F., Christensen, C., and Chung, A. (2009a). A Novel Strong-Motion Seismic Network for Community Participation in Earthquake Monitoring. IEEE Instrumentation & Measurement Magazine, 12(6): 8-15. https://doi.org/10.1109/MIM.2009.5338255.

  • Cochran, E.S., Lawrence, J.F., Christensen, C., and Jakka, R.S. (2009b). The Quake-Catcher Network: Citizen Science Expanding Seismic Horizons. Seismological Research Letters, 80 (1): 26-30. https://doi.org/10.1785/gssrl.80.1.26.

  • QCN Publications

Earthquake Detective

• Project Leads:
  • Earthquake Detective Team

• Tool / Instrument:
  • Earthquake Detective - Zooniverse

• Description:

  • Classifying seismic signals can be challenging because each signal is unique. Help us classify the seismograms into whether they contain a seismic signal or not. If they contain a seismic signal, help us classify whether the signal is from an earthquake or from tremor. This project aims to classify types of seismic events such as earthquakes or tremor, which are measured as motion of the surface of the earth. Raw seismic waves cannot be heard, so for this project we altered their frequencies to audible pitches. Volunteers can classify types of events just by listening to them. In classifying the seismic events, we would come to better understand the population of these seismic events and the conditions under which they occur.

  • In this citizen science project, we ask citizens to listen to relevant sections of seismograms that are converted to audible frequencies. Citizen scientists helped identify local seismic events whose recorded signals are much smaller than those associated with the surface waves that have triggered these local events. The local events include small earthquakes as well as tectonic tremor. While progress has been made in understanding how these events might be triggered by surface waves from large teleseismic earthquakes around the world, there is no consensus on its physical mechanism. The aim of our project is to engage the help of citizen scientists to increase general knowledge of triggered seismic events that may or may not occur during transient strain changes, such as from propagating surface waves. A better understanding of triggered seismic events is expected to provide important clues toward a fundamental understanding of how earthquakes nucleate and the physical mechanisms that connect different earthquakes and other slip events. From the volunteers’ classifications we determined that citizen scientists achieve a higher reliability in detecting earthquakes and noise than in detecting tremor or other signals and that citizen scientists more accurately identify earthquake signals than a trained machine-learning algorithm. For tremor classifications we currently depend entirely on humans as no machine has yet learned to detect triggered tremor.

  • About Page

• Purpose:
  • Understand how a fault moves

• Publications:
  • Tang V, Rösler B, Nelson J, Thompson J, van der Lee S, Chao K and Paulsen M (2020) Citizen Scientists Help Detect and Classify Dynamically Triggered Seismic Activity in Alaska. Frontiers in Earth Science. 8:321. doi: 10.3389/feart.2020.00321 - https://doi.org/10.3389/feart.2020.00321

Quest for Quakes Challenge

• Project Leads:

  • The ”Quest for Quakes” challenge is managed by the NASA Tournament Lab established by NASA and the Crowd Innovation Laboratory at Harvard University in 2010 to create the most innovative, efficient and optimal solutions for specific, real-world challenges being faced by NASA researchers. The lab is using Appirio’s topcoder.com crowdsourcing service to host the challenge, which is open to the public and the more than 815,000 members of the topcoder community.

• Tool / Instrument:
  • $25,000 NASA Prize Competition

  • Data for the competition comes from the more than 65 terabytes of data collected from 125 sensors in California and 40 international sensors monitored by the QuakeFinder group, a humanitarian research and development project by Stellar Solutions, Inc., Palo Alto, California.

  • The data for this competition was provided by the QuakeFinder group, a humanitarian research and development project by Stellar Solutions, Inc., Palo Alto, California. QuakeFinder has 125 sensors in California and 40 sensor suites around the world. These ultra-low frequency magnetometers collect and transmit high-rate data to Stellar Solutions’ data center for management and evaluation. Over 65 terabytes of data have been collected from sensors along the San Andreas fault and other faults in California, Chile, Peru, Greece, Indonesia and Taiwan. 

• Description:
  

  • A new NASA challenge is looking for evidence to support a theory that electromagnetic pulses (EMP) may precede an earthquake, potentially offering a warning to those in the quake’s path. The “Quest for Quakes” two-week algorithm challenge seeks to develop new software codes or algorithms to search through data and identify electromagnetic pulses that may precede an earthquake. Some researchers have speculated such pulses originating from the ground near earthquake epicenters could signal the onset of some quakes.

  • The ‘Quest for Quakes’ competitors will attempt to develop new software algorithms to uniquely identify the electromagnetic pulses that may precede an earthquake by days to weeks. Competitors use several electromagnetic indicators that may eventually provide short term (weeks to days) warning for large seismic events. These electromagnetic signals or indicators appear to be related to stress-induced release of charge conductors  deep in the earth, near future earthquake hypocenters.  The indicators manifest themselves as unusual magnetic (unipolar) pulses, large increases in air conductivity near the future epicenter, "earthquake lights" (extreme cases of air ionization), and apparent infra red patterns seen near the epicenter as detected via various IR weather and environmental satellites.
  • Challenge Summary PDF
  • Press Release
  • Challenge.gov Post

• Publications

OpenStreetMap

• Crowd and Cloud - OpenStreetMap Responding to the Gorkha Earthquake
  • Nama Budhathoki (YouTube Video)
  • Dale Kunce Interview