A Machine Learning Model of the Global Ambient Sound Level
Shane V. Lympany – shane.lympany@blueridgeresearch.com
Michael M. James – michael.james@blueridgeresearch.com
Alexandria R. Salton
Matthew F. Calton
Blue Ridge Research and Consulting, LLC
29 N Market St, Suite 700
Asheville, NC 28801

Kent L. Gee
Mark K. Transtrum
Katrina Pedersen
Department of Physics and Astronomy
Brigham Young University
Provo, Utah 84602

Popular version of paper 4aAB4
Presented Thursday morning, December 5, 2019
178th ASA Meeting, San Diego, CA

Work funded by an Army SBIR

Traffic on a busy road, birds chirping, rushing water—these are some of the many sounds that make up the ambient soundscape, or acoustic environment, that surrounds us. The ambient soundscape is produced by anthropogenic (man-made) and natural sources, and, in turn, the ambient sound level affects the behavior and well-being of humans and animals. Therefore, it is important to understand how the ambient sound level varies in space. To answer this question, we developed a machine learning model to predict the ambient sound level at every point on Earth’s land surface, and we used the model to estimate the global impact of anthropogenic noise.
First, we trained a machine learning model to identify the relationships between more than 1.5 million hours of ambient sound level measurements and 37 environmental variables, such as population density, land cover, and climate. The model predicts the median sound level in A-weighted decibels (dBA). (A-weighting adjusts the sound level based on how the human ear perceives loudness.)
We applied the machine learning model to predict the median daytime ambient sound level at every point on Earth’s land surface (Figure 1). The loudest sound levels occur in highly populated areas, and the quietest sound levels occur in dry biomes with few humans or animals.


Figure 1. Median daytime ambient sound level produced by anthropogenic and natural sources.
Next, we estimated the natural sound level (Figure 2) by applying the machine learning model to environmental variables that we modified to remove the influence of humans. The natural sound level is loudest in areas with significant biodiversity, such as rainforests.

Figure 2. Median daytime ambient sound level produced by natural sources only.
The difference between the overall and natural sound levels (Figure 3) is the amount that anthropogenic noise increases the existing ambient sound level above the natural level. Approximately 5.5 billion people and 28 million square kilometers—an area the size of Russia and Canada combined—are affected by anthropogenic noise that increases the ambient sound level by 3 dBA or more. A 3-dBA increase means that anthropogenic noise is about as loud as the natural sound level. Furthermore, approximately 2.2 billion people and 6.1 million square kilometers—an area the size of the Amazon Rainforest—are affected by anthropogenic noise that increases the ambient sound level by 10 dBA or more. A 10-dBA increase means that anthropogenic noise roughly doubles the perceived loudness of the ambient sound level compared to the natural level.

Figure 3. Difference between the overall and natural ambient sound levels.
In this research, we produced the first-ever global maps of the overall and natural ambient sound levels, and we showed that anthropogenic noise impacts billions of people and vast land areas worldwide. Furthermore, our method for modifying environmental variables is a powerful tool that enables us to predict the effects of future scenarios, such as population growth, urbanization, deforestation, and climate change, on the ambient sound level.

 

Share This