Geological citizens help identify earthquakes and tectonic tremors

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It is not yet possible to predict earthquakes, but analyzing the different types of seismic data allows scientists to determine the location and time of each type of earthquake, and thus a better understanding of when and where tectonic slip may occur across devastating earthquakes. Tens of thousands of earthquake stations worldwide are continuously recording local seismic activity, with an output far exceeding what scientists can treat. Here, researchers from Northwestern University have called for more than 2,000 citizen scientists to rescue for crowd-based analysis of seismic recordings, which have been converted into audiovisual format, through the seismological investigator program on the Zooniverse open science platform. They explain that citizens are at least as accurate as machine learning, and they can even pinpoint tectonic tremors, which were previously only possible for trained professionals. The results are published today in Frontiers in Earth Science.

“My goal was to get help exposing these special seismic events because I felt overwhelmed by the fast-growing data mountain that I was checking in my PhD research,” says lead author Vivian Tang, a graduate student in the graduate department. Earth and Planetary Sciences from Northwestern University, Illinois. “With Zooniverse and the seismic investigator team, we offer people everywhere a simple and engaging way to help conduct further scientific research.”

After completing an educational and practice session, each citizen scientist was asked to listen to a random selection from among 2,447 records captured by earthquake stations across Alaska, part of USArray stations across North America. Visual effects were shown along with the audio data. Each recording corresponds to the first 2000 seconds (but is 800 times faster at audible frequencies) after the estimated arrival of each surface wave station from one of the 30 major known earthquakes that occurred somewhere in the world between 2013 and 2018. A wave of distant earthquake reaches an active site Seismic events such as Alaska, where the tectonic plate slides in the Pacific Ocean under North America, may lead to local earthquakes, such as small earthquakes or tectonic tremors, which are a series of thousands of slow and small vibrations deep in the Earth’s crust that may last for days or weeks. Tremors were first discovered in 2001 and since then they have become an important focus of study, as they show us where a tectonic slide occurred without earthquakes, yet they are believed to play a role in the origin of earthquakes.

An audio file of an earthquake accelerates 800 times. Credit: The authors audio recording of the tremor, speeded 800 times. Credit: The authors recorded the sound of seismic noises, speeding 800 times. Credit: the authors

Each recording was submitted to ten different citizens, who had to classify it as an earthquake, tremor, background noise or none of the above. Quickly, seismic recordings of earthquakes usually look like a bumper door, while tremor looks like a train running over railroad tracks, and background noise can look like whistling winds, sparkling tin foil, or radio static. The researchers used the number of citizens agreeing to each classification as a measure of degree of compatibility. A selection of the dataset was also classified by trained seismologists among the authors, while the output from the machine learning algorithm it specifically developed was used to define earthquakes as a measure of citizen performance. Artificial intelligence has not yet been able to determine the tectonic tremor, which until the current study where citizens successfully mastered this task, could only be recognized in seismic data by seismologists.

Citizens reached a collective decision with 91% of the tested registrations. There was greater consensus when earthquakes were classified (74% of recordings with this collective decision had reached the pre-threshold of 40% for majority voting) than tremor (51%) and background noise (66%). When their collective decision was compared to the correct classification, as determined by professional scientists, citizens combined 85% with accuracy in identifying earthquakes, were above 76% of the accuracy of the machine learning algorithm.

The authors concluded that citizen scientists can make a significant contribution to seismology, allowing scientists to process much more data than ever before on their own, thereby helping them better understand processes within the Earth’s crust and predict earthquakes more precisely. The ability of citizens to identify tremors collectively, which artificial intelligence cannot yet do, will be of particular value to this field.

“Seismology can be a resource for other researchers in this field interested in receiving input from an impressive array of volunteer scientists. We highly encourage these researchers to direct us to seismology programs that they would like to see classified, so that we can include them in the seismology investigator, and reclassify volunteer classifications To researchers, “Tang says.

Project recruits assist citizen scientists in classifying seismic events. More information: Frontiers in Earth Science, DOI: 10.3389 / feart.2020.00321, www.frontiersin.org/articles/1….2020.00321 / abstract

Quote: Citizen Scientists Help Geologists Identify Earthquakes and Tectonic Tremors (2020, August 6) Retrieved on August 6, 2020 from https://phys.org/news/2020-08-citizen-scientists-geologists-earthquakes-tectonic.html

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