Spatial and temporal evolution of community resilience to natural hazards in the coastal areas of China

Qin, Wenmin; Lin, Aiming; Fang, Jian; Wang, Lunche; Li, Man

doi:10.1007/s11069-017-2967-3

Cited by 42 publications

(15 citation statements)

References 43 publications

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“…Although such relative estimation provides easily understood comparisons between places and it is useful for benchmarking progress over time and across space, it could under-or overestimate community resilience at a particular location. Third, principal component analysis is an efficient way to identify dominant variables in the CDRI, but it cannot explain the dynamic and overarching nature of community resilience [59]. It is difficult to quantify resilience in many instances because of the qualitative nature of many resilience indicators.…”

Section: Discussionmentioning

confidence: 99%

“…We used the Getis−Ord G* test of spatial autocorrelation to investigate CDRI score clustering or randomness across space in statistical terms. The Getis−Ord Statistics method is an efficient method for expressing the spatial relationship between different samples [59]. In this study, it was used to depict the high-value and low-value clusters of CDRI.…”

Section: Methodsmentioning

confidence: 99%

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Benchmarking Community Disaster Resilience in Nepal

Aksha

Emrich

2020

IJERPH

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Building disaster resilience is a stated goal of disaster risk reduction programs. Recent research emphasizes a need for a greater understanding of community disaster response and recovery capacity so that communities can absorb shocks and withstand severe conditions and progress through the recovery period more efficiently. Nepal, which is prone to a multitude of hazards and having recently experienced a large earthquake in 2015, provides a unique opportunity for exploring disaster resilience in the developing world context. To date, no study investigating community disaster resilience across the entire country of Nepal exists. This study quantifies disaster resilience at Nepal’s village level, primarily using census data. Guided by the Disaster Resilience of Place (DROP) model, 22 variables were selected as indicators of social, economic, community, infrastructure, and environmental resilience. Community resilience was assessed for 3971 village development communities (VDCs) and municipalities while using a principal component analysis. Additionally, a cluster analysis was performed to distinguish spatial patterns of resilience. Analyses reveal differential community disaster resilience across the country. Communities in the capital city Kathmandu and in the western and far western Hill are relatively resilient. While the entire Tarai region, which holds the greatest proportion of Nepal’s population, exhibits relatively low levels of resilience when compared to the rest of the county. The results from this analysis provide empirical evidence with the potential to help decision-makers in the allocation of scarce resources to increase resilience at the local level.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Benchmarking Community Disaster Resilience in Nepal

Aksha

Emrich

2020

IJERPH

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“…In the meantime, conceptual research about disaster vulnerabilities and disaster risks from a resilience perceptive has also witnessed significant growth in China (Lei et al 2014;Xue et al 2018). However, research about resilience at the community level is just emerging, with relevant studies still predominantly focusing on the identification of the essential factors associated with community resilience in China (Li et al 2016;Qin et al 2017). In practice, along with recent global and national policy advocacies, disaster risk reduction programs implemented to enhance community disaster resilience are not uncommon, especially in southwest China (ODI 2015).…”

Section: Introductionmentioning

confidence: 99%

Cross-Cultural Adaptation and Validation of the 10-Item Conjoint Community Resiliency Assessment Measurement in a Community-Based Sample in Southwest China

Cui

Han

2019

Int J Disaster Risk Sci

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Community resilience has received growing attention in disaster risk management policies and practices, especially in China. However, few applicable instruments are available as a baseline for profiling and estimating a community's resiliency in the face of disasters. The purpose of this study is to cross-culturally adapt and validate the original version of the 10-Item Conjoint Community Resiliency Assessment Measurement (CCRAM-10) in China. Our study further investigates if and to what extent community members translate their participation in disaster risk reduction (DRR) activities into perceived community resilience. A Chinese version of CCRAM-10 was generated and applied to 369 participants from a rural and an urban community in southwest China affected by the 2008 Wenchuan Earthquake. Internal consistency reliability and confirmatory factor analyses were performed to test the assessment instrument's applicability. The Communities Advancing Resilience Toolkit Assessment Survey was used to establish the convergent validity for the Chinese version of CCRAM-10. Multiple linear regression models were used to explore the correlations between respondents' participation in activities and their perception of community resilience, while controlling for basic socio-demographic variables. Analysis results demonstrated good internal consistency reliability (Cronbach's alpha = 0.85) and satisfactory convergent validity for the Chinese version of the CCRAM-10. Construct validity was also confirmed (v 2 /df = 2.161; CFI = 0.977; GFI = 0.971; NFI = 0.958; RMSEA = 0.056; SRMR = 0.030). The regression analysis results indicated that respondents' participation in DRR activities was positively correlated with their perception of community resilience. This study contributes to the wider collection of disaster studies by providing a tested tool for assessing community resilience in the context of China. Community workers and practice researchers may be interested in applying CCRAM-10 to evaluate the effect of specific DRR programmatic activities for improving community resilience.

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“…Aka et al (2016) limitedly assessed multi risk disaster resilience on policy products of Government of Cameroon [6]. While Li et al (2016) and Qin et al (2017) used social, economy, and demography dimensions [14][15]. Zou et al (2018) used social media technology to measure resilience on hurricanes in the US [16].…”

Section: Disaster Community Resilience Conceptmentioning

confidence: 99%

Disaster Risk Management in Building Community Resilience, a Case Study: Cisolok, Sukabumi

Shalih¹

2019

Preprint

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The world has agreed that people resilience to immediately recover from disaster should be a priority, considering the increase of disaster hazards as well as scientific and technological advances. Disaster impacts and risks can be reduced along with increasing people or community resilience towards hazards. Many studies have examined and measured the level of disaster resilience but have not reached the holistic aspect of sustainable development on a community scale. This study was carried out in the Cisolok District, Sukabumi, a highly landslide-prone region. This study uses a qualitative approach with a conceptual foundation of interpretative geography and also uses primary and secondary data. Primary data are obtained from field observations, in-depth interviews, and documentation. Secondary data are obtained from literature studies in the collection of text and maps of published scientific works such as textbooks and study reports or research papers. The results of the study show that factors influence to disaster resilience are community capacities (social capital, disaster preparedness, and risk knowledge) and the roles of local institutions. Community resilience assessment efforts play a key role to identify less resilient regions as well as identify other factors that need to be considered by the government and all stakeholders to develop an inclusive and integrated disaster risk management framework in reducing disaster impacts and risks.

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Spatial and temporal evolution of community resilience to natural hazards in the coastal areas of China

Cited by 42 publications

References 43 publications

Benchmarking Community Disaster Resilience in Nepal

Benchmarking Community Disaster Resilience in Nepal

Cross-Cultural Adaptation and Validation of the 10-Item Conjoint Community Resiliency Assessment Measurement in a Community-Based Sample in Southwest China

Disaster Risk Management in Building Community Resilience, a Case Study: Cisolok, Sukabumi

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