Many cities are experiencing a significant decrease of its social, recreational and economic activities. An often unnoticed facet of this change is that within the auditory landscape. Audio levels of urban and nature categories were recorded in February, pre-COVID changes, and again in April. Acoustical analyses showed distinct reduction in urban sound signatures and increased natural sounds.
Humans are the dominant sound makers in most landscapes – from machinery to cars to just being about. Urban lifestyles are often disconnected from nature; the sounds of nature can be rare for city residents. They are there, just overshadowed by human noise. In an urban context, audio data is more comprehensive than its visual counterpart; noise can be detected from kilometers away or emanating from hidden buildings.
Dr. Richard leBrasseur of the Green Infrastructure Performance Lab at Dalhousie University studies the differences between urban and rural landscapes. As part of his ongoing research, he captured the noise dynamics of a Friday rush-hour at a 4-way intersection on February 28 and and April 3, 2020 for 80 seconds in Truro, Nova Scotia.
Recordings were measured in decibels (dB) which is a measure of the intensity of sound pressure level of noise, decibels indicate the relative loudness of sounds. Each 10 dB increase corresponds to roughly a doubling of the average loudness, or noisiness, of the acoustic environment. Typical examples of sound levels include breathing (10 dB), normal conversation (60 dB), chainsaw (110 db), ambulance siren (120 dB), and rocket launch (180 dB). The World Health Organization has stated that regular and prolonged exposure to noise at 85 dB and over is considered hazardous, and 100 dB for just 15 minutes a day can lead to permanent hearing loss.
Urban noise’s average background noise level is about 60 decibels, which is loud enough to raise one’s blood pressure and heart rate, and cause stress, loss of concentration, and loss of sleep. Sirens are a particularly extreme example of the kind of noise inflicted on urban people every day, they ring at a sound-pressure level of 120 decibels —a level that corresponds with the human pain threshold as stated by the World Health Organization.
Noise has been a concern of city dwellers since Roman times, when a law prohibited the driving of chariots through the cobblestone streets of Rome at night. As cities modernized and industrialized, excessive noise was the foremost “quality of life” complaint in New York City. Below, a report on the sources of city noise in New York City in 1900 included this illustration denoting the types of noises in each neighbourhood. (Commission for the study of noise in New York City, 1929)
Yet, there is an urban rhythm to city soundscapes many just don't notice. Studies conclude this urban background noise is comforting to some . Regardless, there are neurobiological mechanisms operating our physiological and psychological reactions to natural noise stimuli. Natural sounds have the capacity to sooth and impact us the ways urban sounds cannot. This is considered biophilia or our genetic predisposition towards all things within nature.
Acoustic ecology, a discipline founded by R. Murray Schafer and his team at Simon Fraser University, seeks “to find solutions for an ecologically balanced soundscape where the relationship between the human community and its sonic environment is in harmony.” Natural sounds have a strong connection to conservation and the importance of ecological awareness. In 1949, Québecois biologists were the first to record the sounds of marine mammals to promote conservation and awareness. The new and evolving field of ecoacoustics (or bioacoustics) is already changing how researchers assess ecosystem health and evaluate human impact.
Much of the research on the benefits of natural sounds point to Attentional Restoration Theory (ART) and Stress Recovery Theory (SRT) which assert the body and brain’s ability to recover from fatigue or passively recharge itself. The human well-being advantages of bioacoustics or listening to natural sounds are many and include reduced heart rate , decreased levels of stress and anxiety, improved positive emotions, and increased productivity.
Capturing Peri-Rural Aural Events
The study recorded in a specific location, corresponding to a recogniseable volume of signatures and carefully selected to provide as much relevant auditory data as possible. Two locations were tested to ensure the five classes of peri-rural noise would be present. The lowest score location was removed. Both were considered a representative subset of the various peri-rural landscapes of Truro. The location is considered not in the urban core of Truro nor the rural hinterland, densely agricultural, or forested area. Recordings of the noise dynamics were taken in the Spring of 2020.
Auditory Capture 1
Friday February 28 at 4:17 pm at each location for a total of 70 seconds. This timeframe is considered pre-COVID-19 social and economic impact. During these recordings, the weather conditions were dry and partially sunny, and with a temperature of 10C.
Auditory Capture 2
Friday April 10 at 4:28 pm for a total of 85 seconds. This timeframe is considered post-COVID-19 social and economic impact. During these recordings, the weather conditions were dry and sunny, and with a temperature of 11C.
Situation of measuring device: iPhone XS, held 115 cm above ground, facing road intersection centre. Synchronized audio-video captured.
Sampling: Audio - 48 kHz sampling rate with 24 bits/sample.
Video: 2160p@24/30/60fps, Single Lens: 12 MP, f/1.8, 26mm (wide), 1/2.55", 1.4µm.
Calibration: 5 seconds clapping at beginning of each recording (removed from dataset for analysis).
Categorising Peri-Rural Aural Events
The auditory output was focused to emphasize those perceptual audio signatures according to human auditory response based on the Acoustic Salience Model (Huang and Elhilali, 2017) and were situated within 5 categories. These aural categories provide the geospatial context for the peri-rural landscape. Overall, these sounds, as a grouping, are considered emblematic of urban areas in contrast with rural or natural areas where a very different set of categories and auditory signatures would occur.
Nature (10 - 50 dB)
Indicates lower level noises such as rustling leaves, waves, wind, birds, rainfall, streams, and others.
Humans (60 - 85 dB)
Indicates anthropomorphic noise from socio-cultural actions such as sports, play, talking, tv/radio/phone, tourism, small tool use, and others.
Urban Life (65 - 95 dB)
Indicates sound coming from an urbanized area such as walkway, sirens, footsteps, bicycles, trains, ships, airplanes, dog barking, and others.
Vehicles (70 - 95 dB)
Indicates engine type, vehicle density and rate, and presence of paved road.
Works (75 -100 dB)
Indicates activities such as construction, manufacturing, agriculture, industry and presence of human economic activities.
Overall, these sounds, as a grouping, are considered emblematic of urban areas in contrast with rural or natural areas where a very different set of categories and auditory signatures would occur.
Analysing Peri-Rural Aural Events
The raw acoustic data was uploaded and analysed with the SINUS Acoustic Multichannel Universal Analysis v3.0 software and were processed within SNR (Signal-to-Noise Ratio) parameters which provided an output in relation to the surrounding acoustic level, this data output allowed for a graphic description of this environmental noise relationship.
The metrics used to describe the acoustic sound events found in the categorization process conducted over the raw acoustic data are briefly described. The duration, the LAeq, the SNR, and the timestamp, crucial for a precise real-time noise mapping, were used to describe each and all of the auditory events identified.
Duration: This was evaluated in seconds and corresponds to the time that the visualization platform would spend to show its values for each Peri-Rural Audial Events categorisation.
LAeq: This is also known as the time-average or equivalent sound level (IEC, 2013), and it stands for the
equivalent of the total sound energy measured over a limited period of time.
SNR: The Signal-to-Noise Ratio is the relation between any noise event’s evaluated power surrounding the event of study.
Visualisation Approach and Procedure
Humans are adept at detecting and recognizing small deviations within a circular form (Wilkinson et al., 1998), thus a straightforward visualisation represented single sound events as concentric circular forms. The color of each circle or 'ripple' was assigned according to the category to which the sound was associated, resulting in five different possible colors in each location.
The radius of the circle was assigned according to the calculated SNR of the sound event in dB and the various colors within the circles were set according to the LAeq value or the average auditory power (dB) as recorded during that timeframe duration of that signature; meanwhile, the SNR was represented by varying the pattern and size of signature fluctuations.
The circle became a direct informative element of the visualization instead of being purely aesthetic and was not generated randomly, but with a defined dB. However, colors and texture were chosen to deliberately enable their visualisation and abstraction such as downscaling and spacing distance to clarify relationships.
While this procedure represents all recorded signatures, it may introduce a cognitive bias and create confusion in order to understand the impact of ambient or contextual sounds, as these are the most prominent representation. The logarithmic scale is complicated, especially in visual comparative terms; but these visualisations do represent the data within an appropriate margin of values.
The goal of this analysis was to develop a visualisation of Truro’s overall peri-rural sonic data. The results serve as a specific audial spatio-temporal analysis which can be correlated against future analyses. Increases in these auditory levels indicate a change of Truro from a more peri-rural landscape to more peri-urban and eventually urban one.
Huang, N., & Elhilali, M. (2017) Auditory salience using natural soundscapes. The Journal of the Acoustical Society of America, 141(3), 2163-2176.
International Electrotechnical Commission (2013) Electroacoustics—Sound Level Meters—Part 1: Specifications (61672-1, I); International Electrotechnical Commission: Geneva, Switzerland.
Wilkinson, F.; Wilson, H.R.; Habak, C. (1998) Detection and recognition of radial frequency patterns. Vis. Res. 38, 3555–3568.
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THE GREEN INFRASTRUCTURE PERFORMANCE LAB
The Green Infrastructure Performance Laboratory
Director, Richard leBrasseur, PhD
Department of Plant, Food, and Environmental Sciences
20 Rock Garden Road, EE Building, Room 223
Truro, Nova Scotia, Canada B2N 5E3