标题: Understanding the nonlinear effects of the street canyon characteristics on human perceptions with street view images

作者: Xu, JW (Xu, Jiwei); Xiong, QQ (Xiong, Qiangqiang); Jing, Y (Jing, Ying); Xing, LJ (Xing, Lijun); An, R (An, Rui); Tong, ZM (Tong, Zhaomin); Liu, YF (Liu, Yanfang); Liu, YL (Liu, Yaolin)

来源出版物: ECOLOGICAL INDICATORS 卷: 154 文献号: 110756 DOI: 10.1016/j.ecolind.2023.110756 出版年: OCT 2023

摘要: Human perceptions represent the psychological experiences and feelings of individuals toward the surrounding environment. It is influenced by various physical elements (e.g., sky, tree, building, etc.) within the street canyon. However, prior research has predominantly relied on field surveys, high-cost methods, and restricted data sources, thereby limiting analyses of the impact of street canyon characteristics on human perceptions. Importantly, the nonlinear effects of street canyon characteristics on human perceptions have not been fully understood by existing studies. Thus, this study employed Baidu Street View images to evaluate street canyon characteristics and human perceptions at a visual level. A random forest regression was then utilized to uncover the nonlinear effects of street canyon characteristics on human perceptions. The results suggested that some street canyon characteristics nonlinearly affected human perceptions. Specifically, the optimal sky proportion within the individual visual field was 15%, and the appropriate thresholds for trees and grass were 17.5% and 1.0%, respectively. Overall, positive perceptions might be increased if the proportion of natural characteristics within street canyons was maintained below the optimal threshold. In addition, threshold effects have been observed in relation to the perception of beauty due to cars, the perception of vitality and security due to roads, and the perception of boredom due to walls. The findings of this study can serve as scientific evidence and inform urban renewal based on a people-oriented approach.

作者关键词: Human perceptions; Baidu Street View; Street environment; Random forest; Nonlinear effect

地址: [Xu, Jiwei; An, Rui; Tong, Zhaomin; Liu, Yanfang; Liu, Yaolin] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Xiong, Qiangqiang] Jiangxi Normal Univ, Sch Geog & Environm, Nanchang 330022, Peoples R China.

[Jing, Ying] Zhejiang Univ, Ningbo Inst Technol, Business Sch, Ningbo 315100, Peoples R China.

[Xing, Lijun] Hubei Univ, Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China.

[Liu, Yanfang; Liu, Yaolin] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China.

[Liu, Yanfang; Liu, Yaolin] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan 430079, Peoples R China.

通讯作者地址: Liu, YL (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: jiwe_xu@whu.edu.cn; qiangqiang_xiong@163.com; y.crystal@nit.zju.edu.cn; flygirlxlj@163.com; sres@whu.edu.cn; tongzm2215@126.com; yanfangliu88@163.com; yaolin610@163.com

影响因子：6.9