太阳成8722(中国)有限公司-GREEN NO.1

旧版入口
|
English
科研动态
陈慧婷(博士生)、刘耀林的论文在TRAVEL BEHAVIOUR AND SOCIETY 刊出
发布时间:2024-03-21     发布者:易真         审核者:     浏览次数:

标题: Enhancing flood-response commuting resilience via driving mechanism investigation: New evidence from Wuhan, China

作者: Chen, HT (Chen, Huiting); Zhang, HX (Zhang, Hongxin); Tong, ZM (Tong, Zhaomin); Jing, Y (Jing, Ying); Zhang, L (Zhang, Lin); Liu, S (Liu, Sui); Zhang, Y (Zhang, Yan); Chen, CZ (Chen, Cuizhen); Liu, YL (Liu, Yaolin)

来源出版物: TRAVEL BEHAVIOUR AND SOCIETY  : 35  文献号: 100743  DOI: 10.1016/j.tbs.2024.100743  提前访问日期: JAN 2024   出版年: APR 2024  

摘要: In the context of climate change, transportation resilience to flood threats has received significant attention. However, measures to improve practical resilience have not been addressed and elucidated. Various studies from the domains of disaster and transport have been devoted to commuting vulnerability analysis and transport network robustness assessment, whereas a systematic perspective is rarely used to analyze the damage mechanism of floods to the commuting system. To fill this research gap, we constructed an index system from the dimensions of hazard, transport network condition, and commuting pattern as driving factors of commuting risk during floods. The contribution to commuting loss was first assessed to guide intervention prioritization based on flood modeling and commute simulation. We adopted gradient boosting decision trees to examine the relationship between driving factors from three dimensions and commuting. The results of this study conducted in Wuhan indicate that the contribution rate of commuting pattern is the highest, followed by hazard, and finally road network conditions. The effective thresholds of the driving factors were also identified to guide urban governance. This study is a novel exploration of disaster impact mechanism that can provide new insights for the improvement of commuting resilience practices under climate change.

作者关键词: Commuting resilience; Urban flood; Machine learning; Location -based service data; Influencing mechanism

地址: [Chen, Huiting; Zhang, Hongxin; Tong, Zhaomin; Zhang, Lin; Liu, Sui; Liu, Yaolin] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

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

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

[Jing, Ying] NingboTech Univ, Business Sch, Ningbo 315100, Peoples R China.

[Zhang, Yan] Minist Nat Resources, Land Consolidat & Rehabil Ctr, Beijing 100035, Peoples R China.

[Chen, Cuizhen] Wuhan Inst Water Sci Researching Hubei Prov, Wuhan 430014, 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: Huiting_Chen@whu.edu.cn; y.crystal@nit.zju.edu.cn; lynnzhang@whu.edu.cn; yaolin610@yeah.net

影响因子:5.2


Baidu
sogou