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Does social perception data express the spatio-temporal pattern of perceived urban noise? A case study based on 3,137 noise complaints in Fuzhou, China

Lian-Huan GuoSchool of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou 350108, ChinaShi ChengSchool of Architecture, Southeast University, Nanjing 210096, ChinaJiang LiuSchool of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou 350108, ChinaYiyang WangDepartment of Forest Resources Management, University of British Columbia, Vancouver, CanadaYangsheng CaiState Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510640, ChinaXin-Chen HongSchool of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou 350108, China
2022en
ABI

Аннотация

The impact of urban noise on residents' physical health and mental condition has gradually become a hot topic of public discussion. A single urban noise monitoring cannot fully reflect the public's actual perception and feeling of noise. In contrast, social perception data can provide indirect data reference for the public's perception of noise. This study first collected and synthesized public noise complaint data from the government complaint platform. Furthermore, the spatial and temporal distribution characteristics of noise complaints in urban blocks were analyzed to explore the relationship between noise complaint behaviours and The Point of Interest (POI) distribution. The results show that: 1) In the time dimension, the total number of complaints at night is 2,157 and that in the daytime is 980. Furthermore, the number of noise complaints at night is much more than the number of noise complaints during the day; 2) In the spatial dimension, different types of noise complaints have obvious aggregation characteristics. Specifically, construction noise complaints are relatively concentrated, with some 1,813 complaints, while life and business noise complaints are scattered, with several 1,324 complaints; 3) Noise complaints have a specific correlation with the distribution of different types of POIs, among which the correlation is highest with living commercial and residential locations; 4) Places with higher and more abundant POIs are prone to higher noise complaints. This study can provide some ideas for promoting the optimization of urban noise problems.

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