title: Detection and classification of motor vehicle noise in a forested landscape.
abstract: Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.
authors.affiliation: Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, AK, USA, clbrown12@alaska.edu.
authors.forename: Casey L
authors.initials: CL
authors.lastname: Brown
authors.forename: Sarah E
authors.initials: SE
authors.lastname: Reed
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Dietz
authors.forename: Kurt M
authors.initials: KM
authors.lastname: Fristrup
mesh_terms: D002140:California; D003625:Data Collection / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D018986:Motor Vehicles / Q000145:classification / Q000706:statistics & numerical data*; D009624:Noise, Transportation; D013018:Sound Spectrography / Q000295:instrumentation / Q000379:methods; D014197:Trees