Emergency critical link identification framework for large-scale urban network

Confronting the ever-increasing challenges of emergency management in large-scale urban, effective identification of vulnerable and important links that undermine emergency efficacy is a proactive task for disaster prevention and resilience. This work elucidates the definition of emergency critical link by synthesizing failure probability (vulnerability) and failure consequences (importance), and proposes an emergency critical link identification framework for large-scale urban networks from the perspective of urban function and spatial distribution, systematically integrating topology, traffic flow, land-use pattern attributes. The proposed framework employs objective weighting and comprehensive evaluation methods, demonstrating superiority in both identification accuracy and computational efficiency. Real-world datasets comprising urban network, taxi GPS and Points of interest collected in Shenzhen, China, are utilized for framework validation. Results of the emergency critical link identification confirm the validity and applicability of the proposed framework, directly serving to inform regular emergency management and resilient urban development.

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Publication Details

Published
2025-10-15
DOI
https://doi.org/10.1117/12.3077062
Primary Topic
Network Security and Intrusion Detection
Type
article
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article

Emergency critical link identification framework for large-scale urban network

Hao Tian, Xia Luo, Zhengyan Huo
Network Security and Intrusion Detection
article

Emergency critical link identification framework for large-scale urban network

Hao Tian, Xia Luo, Zhengyan Huo
article en

Abstract

Confronting the ever-increasing challenges of emergency management in large-scale urban, effective identification of vulnerable and important links that undermine emergency efficacy is a proactive task for disaster prevention and resilience. This work elucidates the definition of emergency critical link by synthesizing failure probability (vulnerability) and failure consequences (importance), and proposes an emergency critical link identification framework for large-scale urban networks from the perspective of urban function and spatial distribution, systematically integrating topology, traffic flow, land-use pattern attributes. The proposed framework employs objective weighting and comprehensive evaluation methods, demonstrating superiority in both identification accuracy and computational efficiency. Real-world datasets comprising urban network, taxi GPS and Points of interest collected in Shenzhen, China, are utilized for framework validation. Results of the emergency critical link identification confirm the validity and applicability of the proposed framework, directly serving to inform regular emergency management and resilient urban development.

Southwest Jiaotong University (CN)
Openalex Percentile: Top 65%
Network Security and Intrusion Detection
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Emergency critical link identification framework for large-scale urban network — Hao Tian, Xia Luo, et al. · (2025) | TGRS Research Map | TGRS