Measuring County Resilience After the 2008 Wenchuan Earthquake

Xiaolu Li; Nina Lam; Yi Qiang; Kenan Li; Lirong Yin; Shan Liu; Wenfeng Zheng

doi:10.1007/s13753-016-0109-2

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Article Navigation > International Journal of Disaster Risk Science > 2016 > 7(4): 393-412

Xiaolu Li, Nina Lam, Yi Qiang, Kenan Li, Lirong Yin, Shan Liu, Wenfeng Zheng. Measuring County Resilience After the 2008 Wenchuan Earthquake[J]. International Journal of Disaster Risk Science, 2016, 7(4): 393-412. doi: 10.1007/s13753-016-0109-2

Citation:

Xiaolu Li, Nina Lam, Yi Qiang, Kenan Li, Lirong Yin, Shan Liu, Wenfeng Zheng. Measuring County Resilience After the 2008 Wenchuan Earthquake[J]. International Journal of Disaster Risk Science, 2016, 7(4): 393-412. doi: 10.1007/s13753-016-0109-2

Citation:

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Measuring County Resilience After the 2008 Wenchuan Earthquake

doi: 10.1007/s13753-016-0109-2

Xiaolu Li^1,2,
Nina Lam²,
Yi Qiang³,
Kenan Li²,
Lirong Yin⁴,
Shan Liu¹,
Wenfeng Zheng^{1,2
,
,}

1 School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China;
2 Department of Environmental Sciences, Louisiana State University, Baton Rouge, LA 70803, USA;
3 The Earth Lab, University of Colorado Boulder, Boulder, CO 80303, USA;
4 Geographical&Sustainability Sciences Department, University of Iowa, Iowa City, IA 52242, USA

Funds:

This article is partially based on work supported by the US National Science Foundation (Award number 1212112) and the Louisiana Sea Grant program, the China Postdoctoral Science Foundation (No. 2016M592647), the National Natural Science Foundation of China (Grant No. 61305022), and the Opening Fund of State Key Laboratory of Virtual Reality Technology and Systems (Beihang University) (Grant No. BUAA-VR-16KF-11). Views, findings, conclusions, and recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the funding agencies.

Available Online: 2021-04-26

Abstract

Abstract

The catastrophic earthquake that struck Sichuan Province, China, in 2008 caused serious damage to Wenchuan County and surrounding areas in southwestern China. In recent years, great attention has been paid to the resilience of the affected area. This study applied the resilience inference measurement (RIM) model to quantify and validate the community resilience of 105 counties in the impacted area. The RIM model uses cluster analysis to classify counties into four resilience levels according to the exposure, damage, and recovery conditions. The model then applies discriminant analysis to quantify the influence of socioeconomic characteristics on the county’s resilience. Analysis results show that counties located at the epicenter had the lowest resilience, but counties immediately adjacent to the epicenter had the highest resilience capacities. Counties that were farther away from the epicenter returned to normal resiliency quickly. Socioeconomic variables—including sex ratio, per capita GDP, percent of ethnic minority, and medical facilities—were identified as the most influential characteristics influencing resilience. This study provides useful information to improve county resilience to earthquakes and support decision making for sustainable development.
- China,
- Resilience,
- Resilience inference measurement (RIM) model,
- Vulnerability,
- Wenchuan earthquake

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References(68)

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