Earthquake monitoring in urban settings is essential but challenging, due to the strong
anthropogenic noise inherent to urban seismic recordings. Here, we develop a deep …

Proper classification of nontectonic seismic signals is critical for detecting microearthquakes
and develo** an improved understanding of ongoing weak ground motions. We use …

Seismologists are eagerly seeking new and preferably low‐cost ways to map and track
changes in the complex structure of the top few kilometers of the crust. By understanding it …

Ambient seismic noise consists of emergent and impulsive signals generated by natural and
anthropogenic sources. Develo** techniques to identify specific cultural noise signals will …

The fast‐growing interests in high spatial resolution of seismic imaging and high temporal
resolution of seismic monitoring pose great challenges for fast, efficient, and stable data …

Correct identification and modeling of anthropogenic sources of ground motion are of
considerable importance for many studies, including detection of small earthquakes and …

Random noise suppression can greatly improve the signal-to-noise ratio (SNR) of seismic
signals. To suppress random seismic noise, we propose an unsupervised deep neural …

Seismic velocities in rocks are highly sensitive to changes in permanent deformation and
fluid content. The temporal variation of seismic velocity during the preparation phase of …

We image the shallow seismic structure across the Southern San Andreas Fault (SSAF)
using signals from freight trains and trucks recorded by a dense nodal array, with a linear …

We use a dense seismic array of 1,108 vertical‐component geophones within a 600‐m
footprint to detect thousands of small earthquakes near an active strand of the San Jacinto …