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提高城市交通对自然灾害的抵御能力:以中国长春为例。

Improving the resilience of urban transportation to natural disasters: the case of Changchun, China.

作者信息

Wan Ziyang, Lang Qiuling, Zhang Yichen, Zhang Jiquan, Chen Yanan, Liu Gexu, Liu Huanan

机构信息

College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.

Institute of Natural Disaster Research, School of Environment, Northeast Normal University, Changchun, 130024, China.

出版信息

Sci Rep. 2025 Jan 7;15(1):1116. doi: 10.1038/s41598-024-84672-x.

DOI:10.1038/s41598-024-84672-x
PMID:39774268
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11706990/
Abstract

This study quantitatively assesses the resilience of the urban transport system in Changchun under extreme climatic conditions, focusing on the impacts of natural disasters such as snowstorms, strong winds and extreme low temperatures on the transport system. The vulnerability, exposure, and emergency recovery capacity of the transport system in Changchun were analyzed by constructing a comprehensive assessment framework combining multi-criteria decision analysis (MCDM) and geographic information system (GIS). Based on the meteorological and traffic data of Changchun City in the past 10 years, key indicators such as traffic network density, emergency resource distribution, traffic flow, and extreme weather frequency were selected in this study. The weights were calculated by the improved hierarchical analysis method (AHP) and entropy weighting method, and finally the traffic resilience of Changchun city was quantitatively analyzed. The results show that there are significant spatial differences in the toughness of the transport system in Changchun, of which 38.6% of the areas have very low toughness and are concentrated in the urban fringe and urban-rural areas; 25.3% of the areas are at a medium level of toughness; and 5.4% of the areas show high toughness and are mainly located in the city center and important transport hubs. This study proposes transport resilience enhancement strategies for different areas of Changchun, with special recommendations for strengthening infrastructure development, optimizing traffic management and emergency response capacity in low resilience areas. The results of this study provide a scientific basis for Changchun to cope with future extreme climate challenges, and a reference framework for other cities with similar climatic conditions.

摘要

本研究定量评估了长春市城市交通系统在极端气候条件下的恢复力,重点关注暴风雪、强风、极端低温等自然灾害对交通系统的影响。通过构建多准则决策分析(MCDM)与地理信息系统(GIS)相结合的综合评估框架,分析了长春市交通系统的脆弱性、暴露性和应急恢复能力。基于长春市过去10年的气象和交通数据,本研究选取了交通网络密度、应急资源分布、交通流量、极端天气频率等关键指标。采用改进的层次分析法(AHP)和熵权法计算权重,最终对长春市的交通恢复力进行了定量分析。结果表明,长春市交通系统韧性存在显著的空间差异,其中38.6%的区域韧性极低,集中在城市边缘和城乡结合部;25.3%的区域韧性处于中等水平;5.4%的区域韧性较高,主要位于市中心和重要交通枢纽。本研究针对长春市不同区域提出了交通恢复力提升策略,特别建议加强低恢复力区域的基础设施建设、优化交通管理和应急响应能力。本研究结果为长春市应对未来极端气候挑战提供了科学依据,并为其他气候条件相似的城市提供了参考框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/f0fd251778cf/41598_2024_84672_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/1dc692722e14/41598_2024_84672_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/1dc692722e14/41598_2024_84672_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/4ddc83b6b0ba/41598_2024_84672_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/65f276587dc9/41598_2024_84672_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/ef4ab47d0d8e/41598_2024_84672_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/ed4a2838ee63/41598_2024_84672_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/185f58679cfc/41598_2024_84672_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/87c9d30cbe48/41598_2024_84672_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/4ce967ec43f7/41598_2024_84672_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/9ca82343b244/41598_2024_84672_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/2b31bcb960f0/41598_2024_84672_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34f6/11706990/f0fd251778cf/41598_2024_84672_Fig11_HTML.jpg

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