AI is providing an early warning system for volcanoes on the verge of blowing their top.
What happened: Researchers at the University of Leeds developed a neural net that scans satellite data for indications that the ground near a volcano is swelling—a sign it may be close to erupting.
How it works: Satellites carrying certain sensors can track centimeter-scale deformations of Earth’s crust. Seismologists in the 1990s figured out how to manually read this data for signs of underground magma buildups. However, human eyeballs are neither numerous nor sharp enough to monitor data for all of Earth’s 1,400 active volcanoes.
- Matthew Gaddes, Andy Hooper, and Marco Bagnardi trained their model using a year’s worth of satellite imagery leading up to the 2018 eruption of a volcano in the Galapagos Islands.
- Data came from a pair of European satellites that passed over the volcano every 12 days.
- The model differentiates rapid ground-level changes associated with catastrophic eruptions from slower, more routine deformations.
Behind the news: Researchers at the University of Bristol developed a similar method to measure deformations in the Earth’s crust using satellite data. However, their model can be fooled by atmospheric distortion that produces similar signals in the data. The Leeds and Bristol groups plan to collaborate in side-by-side tests of their models on a global dataset in the near future. Another group based at Cornell University is attempting to make similar predictions through satellite data of surface temperature anomalies, ash, and gaseous emissions.
Why it matters: Approximately 800 million people live within the blast zones of active volcanoes, and millions of sightseers visit their slopes each year. On Monday, New Zealand’s White Island volcano erupted, killing at least five tourists.
We’re thinking: If researchers can scale their model up to cover the entire globe, they’ll deserve applause that thunders as loudly as Krakatoa.