摘要
城市严重的交通噪声污染危害公众健康,亟待改善。我国城市层面的噪声管控缺乏广泛普及的噪声识别工具,而多源数据的发展,为城市中噪声的快速评估提供了新可能。以大连市典型城区为例,以城市地块为研究单元,分析城市多源数据与交通噪声的关联性,并探究基于多源数据建立交通噪声预估模型的可行性。研究发现,街景图像数据、空间句法指标、兴趣点(Point of Interest,POI)数据均与交通噪声存在显著相关性。以三类数据分别建立回归模型,均可以解释一定程度交通噪声。研究可助力城市规划层面的噪声防控。
Serious traffic noise pollution in cities endangers public health and needs to be improved.China’s city-level noise control lacks widely available noise identification tools,and the development of multi-source data provides new possibilities for rapid assessment of noise in cities.Taking the typical urban area of Dalian as an example,this paper analyzes the correlation between urban multi-source data and traffic noise by taking urban land as the research unit,and explores the feasibility of establishing a traffic noise estimation model based on multi-source data.It is found that street view image data,spatial syntax index,and Point of Interest(POI)data are significantly correlated with traffic noise.The research can help prevent and control noise at the urban planning leve.
作者
王涛
路晓东
崔晓鸥
WANGT Tao;LU Xiaodong;CUI Xiaoou(School of Architecture and Fine Arts,Dalian University of Technology,Dalian 116000,China)
出处
《电声技术》
2022年第12期42-45,共4页
Audio Engineering
基金
国家自然科学基金(51878110)
关键词
交通噪声
预测模型
多源数据
多元线性回归
traffic noise
prediction model
multiple source data
multiple linear regression
作者简介
王涛(1997—),男,硕士,研究方向为城市噪声环境;通信作者:路晓东(1977—),男,博士,教授,研究方向为城市噪声环境。E-mail:lxd3721@163.com。
