{"title":"Network invulnerability modeling of daily necessity supply based on cascading failure considering emergencies and dynamic demands","authors":"Hao Huang , Wenchu Zhang , Zipei Zhen , Haochen Shi , Miaoxi Zhao","doi":"10.1016/j.jag.2024.104225","DOIUrl":null,"url":null,"abstract":"<div><div>Confronting the escalating challenge of emergencies, the urban supply network of daily necessity is an important defense line for human well-being. This study introduces a groundbreaking approach that leverages mobile signaling data, departing from static regional data, to model large-scale and high-precision urban supply-demand network. Moreover, a significant stride in assessing network invulnerability is presented by incorporating cascading failure and emphasizing demand-side factors in attack strategy simulations. This approach marks a paradigm shift in network invulnerability simulation: moving from network topology characteristics to a human-centric approach, which helps better identify vulnerable zones. The model’s robustness is corroborated through simulations of major disaster scenarios. The results indicate that: 1) High-precision human mobility data promises large-scale urban supply-demand network modeling with high accuracy. 2) In regions characterized by greater vulnerability, the establishment of local supply networks demonstrates efficacy in mitigating the impacts of minor disasters. 3) During various stages of cascading failure, the leading factors contributing to community supply shortages vary, with population density being the predominant factor. This research propels the methodology forward, incorporating multi-scenario simulations to augment practicality, and offers valuable insights for urban supply system enhancement.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"134 ","pages":"Article 104225"},"PeriodicalIF":7.6000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843224005818","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Confronting the escalating challenge of emergencies, the urban supply network of daily necessity is an important defense line for human well-being. This study introduces a groundbreaking approach that leverages mobile signaling data, departing from static regional data, to model large-scale and high-precision urban supply-demand network. Moreover, a significant stride in assessing network invulnerability is presented by incorporating cascading failure and emphasizing demand-side factors in attack strategy simulations. This approach marks a paradigm shift in network invulnerability simulation: moving from network topology characteristics to a human-centric approach, which helps better identify vulnerable zones. The model’s robustness is corroborated through simulations of major disaster scenarios. The results indicate that: 1) High-precision human mobility data promises large-scale urban supply-demand network modeling with high accuracy. 2) In regions characterized by greater vulnerability, the establishment of local supply networks demonstrates efficacy in mitigating the impacts of minor disasters. 3) During various stages of cascading failure, the leading factors contributing to community supply shortages vary, with population density being the predominant factor. This research propels the methodology forward, incorporating multi-scenario simulations to augment practicality, and offers valuable insights for urban supply system enhancement.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.