Noise and the city: Leveraging crowdsourced big data to examine the spatio-temporal relationship between urban development and noise annoyance

Abstract

Noise is one of the most frequently complained nuisances and public health hazards. While traffic-related noise has been studied extensively, research on construction noise has been lacking. In this study, we examined the relationship between construction activities and noise annoyance and tested whether this relationship is stronger during after-hours. Data were drawn from a historical inventory of major development projects and crowdsourced citizen complaints data (311 calls) in Vancouver, Canada from 2011 to 2016. Mixed effects models were developed with an interaction between construction activities and after-hours report. Results show that neighborhood noise complaints were significantly associated with major constructions (IRR = 1.062, 95% CI = 1.024-1.097). A significant interaction effect was also found between construction activities and after-hours reporting (IRR = 1.050 CI = 1.012-1.087). To our knowledge, this is one of the first studies to empirically show adverse effects of urban development on noise annoyance. Results imply that existing noise bylaws may not be effective in restricting construction activities at night and during sleeping hours that may cause adverse health effects.

Mitigating Bias in Big Data for Transportation

“…Despite these challenges, big data "can reveal new dynamics, can allow for the study of certain processes in real time and can highlight relationships and correlations that may pass unnoticed using classical methods and data" (Shearmur 2015). Big data can lead to insights at spatial and temporal scales not previously possible (Zhou et al 2019;Hong et al 2019). Through new insights on the use of big data in transportation and smart cities, this study supports both the research and practice of transportation planning.…”

Analysis of Environmental Issues with an Application of Civil Complaints: The Case of Shiheung City, Republic of Korea

“…Hong et al [42] studied crowdsourced big data based on noise complaints from the 311 system, which is the full-time non-emergency telephone services and online platform, in Vancouver, British Columbia, Canada. The utilized 311 data were classified as either “noise complaint case” or “general noise inquiry case” from 2011 to 2016, and were compared with the location and geographic information of noise.…”

Relationship between urban development patterns and noise complaints in England

“…Making a noise complaint is a behaviour related to noise level and perception. A general assumption is that not everyone who experiences noise issues complains; however, noise complaints can give useful indications regarding those areas in which people are bothered by noise (Hong et al, 2019;Public Health England, 2018).…”

“…Zheng et al (2014) developed a model to recover the noise situation throughout NYC where they used noise complaint data. Hong et al (2019) found, using longitudinal administrative data from 2011 to 2016, that an increase in construction activity of one-unit in a cell based on heat maps was associated with an approximately 6% higher incidence rate of noise complaints. However, the research on how urban planning affects noise complaints is currently inadequate.…”