Modeling and characterizing urban infrasonic and low-frequency noise in the Las Vegas, NV regiona).

Empirical models of ambient infrasound noise are valuable tools for assessing the detection capabilities of infrasound networks on local to global scales. Models that characterize noise in unpopulated, quiet environments are well established, and there is a detailed understanding of the sources that contribute to rural noise profiles. However, there is a research gap for infrasound and low-frequency noise in urban environments, based on the assumption that high noise levels generated by human activity will render signals of interest, such as earthquakes and explosions, undetectable.

Monitoring changes in human activity during the COVID-19 shutdown in Las Vegas using infrasound microbarometers.

While studies of urban acoustics are typically restricted to the audio range, anthropogenic activity also generates infrasound (<20 Hz, roughly at the lower end of the range of human hearing). Shutdowns related to the COVID-19 pandemic unintentionally created ideal conditions for the study of urban infrasound and low frequency audio (20-500 Hz), as closures reduced human-generated ambient noise, while natural signals remained relatively unaffected. An array of infrasound sensors deployed in Las Vegas, NV, provides data for a case study in monitoring human activity during the pandemic through urban acoustics.

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network.

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields).