Multitimescale template matching: discovering eruption precursors across diverse volcanic settings
Volcanic eruptions pose significant risks, demanding precise monitoring for timely hazard
mitigation. However, interpreting noisy seismic data for eruptive precursors remains …
mitigation. However, interpreting noisy seismic data for eruptive precursors remains …
Eruption forecasting model for Copahue volcano (southern Andes) using seismic data and machine learning: A joint interpretation with geodetic data (GNSS and …
Anticipating volcanic eruptions remains a challenge despite significant scientific
advancements, leading to substantial human and economic losses. Traditional approaches …
advancements, leading to substantial human and economic losses. Traditional approaches …
Single‐station multiparametric seismic monitoring of Copahue Volcano, Argentina–Chile (2018–2023)
Abstract Knowledge about the temporal evolution of a volcano is fundamental for an
accurate understanding of the occurring physical dynamic processes and an appropriate …
accurate understanding of the occurring physical dynamic processes and an appropriate …
[HTML][HTML] Identifying earthquake swarms at Mt. Ruapehu, New Zealand: a machine learning approach
S Mitchinson, JH Johnson, B Milner… - Frontiers in Earth Science, 2024 - frontiersin.org
Mt. Ruapehu is an active andesitic stratovolcano, consisting of several peaks with the
summit plateau at 2,797 m, making it the tallest active volcano in New Zealand. The extent of …
summit plateau at 2,797 m, making it the tallest active volcano in New Zealand. The extent of …