System resilience assessment method of urban lifeline system for GIS

Huang, Wenjie; Ling, Mengzhi

doi:10.1016/j.compenvurbsys.2018.04.003

Cited by 28 publications

(7 citation statements)

References 34 publications

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“…The U.S. Critical Infrastructure Protection Board identifies critical infrastructure in cities as telecommunications, electric systems, gas and oil systems, banking and finance, transportation, water systems, government services, and emergency services. Together, these critical infrastructures form urban lifeline systems that play an essential role in improving the quality of urban services and the standard of living of urban residents [16]. The combination of digital technology and physical urban infrastructure has given rise to the concept of smart infrastructure [17].…”

Section: Concepts and Research Statuses Of Traditional And New Infras...mentioning

confidence: 99%

Decision-Making Based on Network Analyses of New Infrastructure Layouts

Wang

Zhang

et al. 2022

Buildings

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New Infrastructure (NI) has gradually become a new driving force for regional economic growth and an important part of the construction of new urban infrastructure in many countries, including China. Compared with traditional infrastructures, these NIs have mutually supportive functions and complex interrelationships that create interconnected networks of resources, information, and other interactions during the construction of the NIs. Therefore, it is important to analyze such correlation networks and explore their formation mechanisms in order to develop more scientific and reasonable strategies for NI investment and construction. In this study, the interdependence between NIs in Chongqing was analyzed as an example. Social network analysis (SNA) was used for the overall characteristics of the interdependency network of the NIs and an exponential random graph model (ERGM) was used to reveal the formation mechanism of this network. The results showed that information infrastructure is the key node for enhancing the effectiveness of Chongqing’s NI needs and its government should play a coordinating role. The network of related relationships is characterized by “reciprocity” and “small group”. The aggregation of NIs with such characteristics can produce an agglomeration effect. So, in the planning of NIs, the coordination among management departments should be strengthened and project locations should be reasonably arranged according to the functional interactive characteristics of the projects.

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Section: Concepts and Research Statuses Of Traditional And New Infras...mentioning

confidence: 99%

Decision-Making Based on Network Analyses of New Infrastructure Layouts

Wang

Zhang

et al. 2022

Buildings

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“…considered that water system has the characteristics of resilience [ 25 ]. Huang and Ling used GIS spatial analysis and ABM model to study the resilience of urban water resources system [ 8 ]. Sun and Meng introduced “soft power” factors such as culture and system into the evaluation index system of regional water system resilience [ 19 ], and so on.…”

Section: Introductionmentioning

confidence: 99%

A Three-Way Decision Approach for Water Resources System Resilience Evaluation and Its Application

Yang

Wang²,

Zhao³

et al. 2022

Water Resour

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Resilience is a significant uncertainty thought of water resources system security. Compared with risk analysis, resilience pays more attention to the ability of water resources system itself to deal with adverse events. However, a standard system of water resources system resilience’s concept and evaluation have not yet formed. In view of this, this study had attempted to decompose the process of resisting interference of water resources system and analyzed the characteristics and influencing factors of three sub processes of resistance, recovery and adaptation. Furtherly, a new resilience evaluation index system of water resources system was explored and a three-way dicision approach for water resources system resilience analysis based on variable fuzzy sets and partial connection number was developed. Specifically, a multi-grade quantitative evaluation of water resources resilience was carried out based on variable fuzzy sets method, and then the quantitative evaluation results were transformed into qualitative decision-making results using a new three-way decision model based on partial connection number of set pair analysis. Finally, a case study of China’s Yangtze River Economic Belt (YEB) in 2008–2017 was performed and the results show that the resilience of water resources system in the YEB does not show an obvious improvement trend, or even almost stagnant. Of the 110 samples, 83.6% were at the medium level. Only 6.4% are barely at the excellent level, but they are basically in Shanghai.

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“…When it comes to vulnerability or resilience assessment, geographic information systems (GIS) have become powerful tools for identifying vulnerable communities and locations, at different scales [37][38][39]. There are also many studies that have conceived different GIS methods to predict, evaluate, and analyze the vulnerability and resilience of social environmental systems [40][41][42][43][44]. GIS can help governments, environmental agencies, and insurance companies to improve prevention, early warning mechanisms, and mitigation efforts using predictive analytics.…”

Section: Introductionmentioning

confidence: 99%

Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China

Xiang

Proverbs

2020

Water

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While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.

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System resilience assessment method of urban lifeline system for GIS

Cited by 28 publications

References 34 publications

Decision-Making Based on Network Analyses of New Infrastructure Layouts

Decision-Making Based on Network Analyses of New Infrastructure Layouts

A Three-Way Decision Approach for Water Resources System Resilience Evaluation and Its Application

Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China

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