A synthesis of disaster resilience measurement methods and indices

Cai, Heng; Lam, Nina Siu‐Ngan; Qiang, Yi; Zou, Lei; Correll, Rachel M.; Mihunov, Volodymyr V.

doi:10.1016/j.ijdrr.2018.07.015

Cited by 187 publications

(106 citation statements)

References 18 publications

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“…Authors from other countries indicate that there are many research approaches in resilience assessment [29,45,46] (this article considers the adaptability as part of this body), and the conclusion that comes from the analysis of this part of the literature on the subject is that it is recommended that a combination of many of research approaches is used [47]. Figure A3.…”

Section: Discussionmentioning

confidence: 99%

The Comparative Analysis of the Adaptability Level of Municipalities in the Nysa Kłodzka Sub-Basin to Flood Hazard

et al. 2020

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A municipality is a basic local government unit (LGU) in Poland. It is responsible for the safety of its citizens, especially in circumstances of flood hazard. A municipality is a unique social-ecological system (SES), distinguished by its ability to adapt to flood hazard. It is impossible to specify the conditions a municipality has to reach to achieve the highest adaptability to flood hazard, however, it is possible to assign a level of adaptability to a municipality, one that corresponds to the position of a given municipality among the population of assessed municipalities threatened by floods. Therefore, a tool was developed to rank municipalities by their adaptability on the assumption that the assessment of municipal adaptability was influenced by 15 selected features. The research was carried out using data from the period of 2010-2016 for 18 municipalities-SESs located in the Nysa Kłodzka sub-basin. It was indicated that municipalities located in the higher course of the river possess higher levels of adaptability. At the same time, the size of a flood stands for each municipality position with regards to the synthetic adaptability index (SAI).

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Section: Discussionmentioning

confidence: 99%

The Comparative Analysis of the Adaptability Level of Municipalities in the Nysa Kłodzka Sub-Basin to Flood Hazard

et al. 2020

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“…Because the result of variable importance by impurity reduction is biased (Strobl et al 2007), many researchers have verified and suggested choosing the MSE reduction method when permuting the variables (Ishwaran 2007;Strobl et al 2008). The MSE reduction method uses the MSE value of the Out-Of-Bag (OOB) data to evaluate the variable importance (Cai et al 2018). It is determined as follows:…”

Section: Random Forest (Rf)mentioning

confidence: 99%

Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

Luo

Yan

McClure

2020

Preprint

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The COVID-19 outbreak has become a global pandemic. Spatial variation in the environmental, health, socioeconomic, and demographic risk factors of COVID-19 death rate is not well understood. Global models and local linear models were used to estimate the impact of risk factors of the COVID-19, but these do not account for the nonlinear relationships between the risk factors and the COVID-19 death rate at various geographical locations. We proposed a local nonlinear nonparametric regression model named geographically weighted random forest (GW-RF) to estimate the nonlinear relationship between COVID-19 death rate and 47 risk factors derived from US Environmental Protection Agency, National Center for Environmental Information, Centers for Disease Control and the US census. The COVID-19 data were employed to a global regression model random forest (RF) and a local model GW-RF. The adjusted R2 of the RF is 0.69. The adjusted R2 of the proposed GW-RF is 0.78. The result of GW-RF showed that the risk factors (i.e. going to work by walking, airborne benzene concentration, householder with a mortgage, unemployment, airborne PM2.5 concentration and percent of the black or African American) have a high correlation with the spatial distribution of the COVID-19 death rate and these key factors driven from the GW-RF were mapped, which could provide useful implications for controlling the spread of COVID-19 pandemic.

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“…Apart from challenges mentioned above regarding lack of data at multiple scales and a shortage of validation, verification, and benchmarking processes, challenges are posed by the lack of balanced representation across social, economic, and environmental systems within communities (Cai et al, 2018;Sharifi, 2016). Lack of representation and balance may indicate limited system understanding and the potential for poor or incomplete assessment results, depending upon the context and intent of assessment.…”

Section: Current Challengesmentioning

confidence: 99%

“…Many community resilience indicator sets appear sparse regarding inclusion of the natural environment, focusing on tree density and impervious surface, and neglecting more complex aspects of community health. In a recent review of disaster resilience measures by Cai et al (2018), environmental and ecological indicators other than land use were found to be applied in six of 174 reviewed articles. Despite growing awareness of long-term resilience and its linkages to the quality and maintenance of natural resources (ecosystem services that provide essential lifeline support and protection mechanisms such as water quality, flood control, green spaces, biodiversity, etc.…”

Section: Current Challengesmentioning

confidence: 99%

Selecting Indicators for Assessing Community Sustainable Resilience

et al. 2019

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Communities are complex systems subject to a variety of hazards that can result in significant disruption to critical functions. Community resilience assessment is rapidly gaining popularity as a means to help communities better prepare for, respond to, and recover from disruption. Sustainable resilience, a recently developed concept, requires communities to assess system‐wide capability to maintain desired performance levels while simultaneously evaluating impacts to resilience due to changes in hazards and vulnerability over extended periods of time. To enable assessment of community sustainable resilience, we review current literature, consolidate available indicators and metrics, and develop a classification scheme and organizational structure to aid in identification, selection, and application of indicators within a dynamic assessment framework. A nonduplicative set of community sustainable resilience indicators and metrics is provided that can be tailored to a community's needs, thereby enhancing the ability to operationalize the assessment process.

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A synthesis of disaster resilience measurement methods and indices

Cited by 187 publications

References 18 publications

The Comparative Analysis of the Adaptability Level of Municipalities in the Nysa Kłodzka Sub-Basin to Flood Hazard

The Comparative Analysis of the Adaptability Level of Municipalities in the Nysa Kłodzka Sub-Basin to Flood Hazard

Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

Selecting Indicators for Assessing Community Sustainable Resilience

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