ABSTRACT
This paper presents the empirical probability density of the power spectral density as a tool to assess the field performance of passive acoustic monitoring systems and the statistical distribution of underwater noise levels across the frequency spectrum. Using example datasets, it is shown that this method can reveal limitations such as persistent tonal components and insufficient dynamic range, which may be undetected by conventional techniques. The method is then combined with spectral averages and percentiles, which illustrates how the underlying noise level distributions influence these metrics. This combined approach is proposed as a standard, integrative presentation of ambient noise spectra.
Subject(s)
Environmental Monitoring/methods , Models, Theoretical , Noise , Signal Processing, Computer-Assisted , Ultrasonics , Environmental Monitoring/instrumentation , Fourier Analysis , Motion , Oceans and Seas , Pressure , Probability , Sound Spectrography , Time Factors , Transducers, Pressure , Ultrasonics/instrumentation , WaterABSTRACT
Rising underwater noise levels from shipping have raised concerns regarding chronic impacts to marine fauna. However, there is a lack of consensus over how to average local shipping noise levels for environmental impact assessment. This paper addresses this issue using 110 days of continuous data recorded in the Strait of Georgia, Canada. Probability densities of ~10(7) 1-s samples in selected 1/3 octave bands were approximately stationary across one-month subsamples. Median and mode levels varied with averaging time. Mean sound pressure levels averaged in linear space, though susceptible to strong bias from outliers, are most relevant to cumulative impact assessment metrics.
