VolcanoesSpeech Recognition Techniques Help Predict Volcanoes’ Behavior
Researchers are aiming to automatically analyze volcanic activities to develop early-warning models that could save the lives of people living near volcanoes. Machine learning has been used for pattern identification in speech recognition, and researchers say the same technique can be used to understand patterns of volcanic “behavior.”
Dr. Luciano Zuccarello grew up in the shadow of Mount Etna, an active volcano on the Italian island of Sicily. Farms and orchards ring the lower slopes of the volcano, where the fertile soil is ideal for agriculture. But the volcano looms large in the life of locals because it is also one of the most active volcanoes in the world.
However, predicting volcano behavior is difficult, especially if they have been dormant, and monitoring them can be challenging since taking samples or deploying equipment poses physical dangers. And while theoretical models may approximate how a particular volcano behaves given its location, geological makeup and the behavior of the Earth’s magma underneath it (amongst other things), there are still many unknown variables – and every volcano is unique.
Now a researcher at the University of Granada in Spain, Zuccarello is aiming to automatically analyze volcanic activities to develop early-warning models that could save the lives of people living near volcanoes.
In the last decade, data collection methods have improved significantly, with new and more sensitive equipment, and researchers now have access to an unprecedented deluge of data. For example, they can access real-time information on how the Earth shakes in the vicinity of the volcano (seismic activity), the propagation of sound waves from deep within the Earth, and the chemicals present inside the volcano and how they are changing.
Volcano observatories need to analyze large quantities of data in a short period of time. “There is a need for faster and error-free techniques to gather such data,” Zuccarello said.
His VOLCANOWAVES project, which includes researchers based in Spain, the United Kingdom, Italy, Mexico, and Argentina, uses machine learning to identify patterns in the seismic activity around a volcano in an effort to predict when, or if it will erupt. In particular, Zuccarello is looking at the low-frequency events, such as volcanic tremors, which are usually linked to the movement of magma within a volcano’s plumbing.
More than 29 million people globally live within 10km of a volcano, and understanding volcanoes’ behavior – and being able to predict when they are going to erupt or spew ash into the air – is vital for safeguarding people’s wellbeing.
