Machine learning (ML) is a collection of methods used to develop understanding and
predictive capability by learning relationships embedded in data. ML methods are becoming …

Soil thermal conductivity (λ) is an important thermal property that is crucial for surface energy
balance and water balance studies. 1602 measured soil thermal conductivity values …

Over the past two decades (2000–2020), volcano infrasound (acoustic waves with
frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of …

Explosions produce low‐frequency acoustic (infrasound) waves capable of propagating
globally, but the spatio‐temporal variability of the atmosphere makes detecting events …

Given the recent developments in machine-learning technology, its application has rapidly
progressed in various fields of earthquake seismology, achieving great success. Here, we …

Infrasound data are used by scientists and monitoring observatories to track shifts in eruptive
behavior, identify signs of unrest, and ultimately help forecast major eruptions. However …

Since various phenomena produce infrasound, including both man-made and natural
sources, the ever-growing dataflow demands automatic processes via machine learning for …

We develop a deep learning-based infrasonic detection and categorization methodology
that uses convolutional neural networks with self-attention layers to identify stationary and …

The Korean infrasound catalogue (KIC) covers 1999–2022 and characterizes a rich variety
of source types as well as document the effects of the time-varying atmosphere on event …

Volcano infrasound data contain a wealth of information about eruptive patterns, for which
machine learning (ML) is an emerging analysis tool. Although global catalogs of labeled …