Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2024-11-23 DOI:10.1016/j.scs.2024.106006

Chengye Ma , Mingxing Song , Weitao Zeng , Xinuo Wang , Tao Chen , Shihai Wu

{"title":"Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts","authors":"Chengye Ma , Mingxing Song , Weitao Zeng , Xinuo Wang , Tao Chen , Shihai Wu","doi":"10.1016/j.scs.2024.106006","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"118 ","pages":"Article 106006"},"PeriodicalIF":10.5000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724008308","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;