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Assessment of social vulnerability to natural hazards in the Yangtze River Delta, China

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Abstract

China is exposed to a wide range of natural hazards, and disaster losses have escalated over the past decade. Owing to the pressure from natural disasters, along with changes in climate, social conditions, and regional environment, assessment of social vulnerability (SV) to natural hazards has become increasingly urgent for risk management and sustainable development in China. This paper presents a new method for quantifying SV based on the projection pursuit cluster (PPC) model. A reference social vulnerability index (SVI) at the county level was created for the Yangtze River Delta area in China for 1995, 2000, 2005, and 2009. The result of social vulnerability assessment was validated using data of actual losses from natural disasters. The primary findings are as follows: (i) In the study area, the major factors that impact SVI are regional per capita GDP and per capita income. (ii) The study area was more vulnerable in 1995 than in later years. SV of the whole region had decreased over the study period. (iii) Most part of Shanghai and the southeast part of Jiangsu Province had been the least vulnerable within the region. From this least vulnerable zone to the periphery of the region, the situation deteriorated. The highest SVI values in all evaluated years were found in the northern, western, or southern tips of the Yangtze River Delta.

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Notes

  1. Here “Jiangsu Province” refers to the southern part of Jiangsu Province and “Zhejiang Province” refers to the northern and eastern part of Zhejiang Province. So does the following text if not stated otherwise.

References

  • Adger WN, Brooks N, Bentham G, Agnew M, Eriksen S (2004) New indicators of vulnerability and adaptive capacity. Technique Report 7, Tyndall Centre for Climate Change Research, Norwich

  • Birkmann J (2006) Measuring vulnerability to natural hazards: towards disaster resilient societies. United Nations University, Tokyo

    Google Scholar 

  • Blaikie P, Cannon T, Davis I, Wisner B (1994) At risk: natural hazards, people’s vulnerability, and disasters. Routledge, New York

    Google Scholar 

  • Burton I, Kates RW, While GF (1978) The environment as hazard. Oxford University Press, New York

    Google Scholar 

  • Chellali F, Khellaf A, Belouchrani A (2012) Identification and analysis of wind speed patterns extracted from multi-sensors measurements. Stoch Environ Res Risk Assess 27(1):1–9

    Google Scholar 

  • Clark GE, Moser SC, Ratick SJ, Dow K, Meyer WB, Emani S, Jin W, Kasperson JX, Kasperson RE, Schwarz HE (1998) Assessing the vulnerability of coastal communities to extreme storms: the case of Revere, MA, USA. Mitig Adapt Strat Glob Change 3(1):59–82

    Article  Google Scholar 

  • Cutter SL (1996) Vulnerability to environmental hazards. Prog Hum Geogr 20(4):529–539

    Article  Google Scholar 

  • Cutter SL, Finch C (2008) Temporal and spatial changes in social vulnerability to natural hazards. Proc Natl Acad Sci USA 105(7):2301–2306

    Google Scholar 

  • Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Social Science Quarterly 84(2):242–261

    Article  Google Scholar 

  • Du J, Fang J, Xu W, Shi P (2012) Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China. Stoch Environ Res Risk Assess 27(1):377–387

    Google Scholar 

  • Dwyer A, Zoppou C, Nielsen O, Day S, Roberts S (2004) Quantifying social vulnerability: A methodology for identifying those at risk to natural hazards. Geoscience Australia Record 2004/14

  • Ebert A, Kerle N, Stein A (2009) Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data. Nat Hazards 48(2):275–294

    Article  Google Scholar 

  • Fan Y, Luo Y, Chen Q (2001) Establishment of weight about vulnerability indexes of a hazard bearing body. Journal of Catastrophology 16:85–87 in Chinese

    Google Scholar 

  • Friedman JH, Tukey JW (1974) A projection pursuit algorithm for exploratory data analysis. IEEE Transactions on Computers C-23 (9), 881–890

    Google Scholar 

  • Ge Y, Liu J, Shi P (2006) Quantifying social vulnerability for flood hazard of households: a case study of Changsha, China. J Nat Disasters 15(6): 29–33 (in Chinese)

    Google Scholar 

  • Ge Y, Liu J, Li F, Shi P (2008) Quantifying social vulnerability for flood disasters of insurance company: a case study of Changsha, China. Journal of Southeast University (Natural Science Edition) 24(sup):147–150

    Google Scholar 

  • Hewitt K (1997) Regions at risk: a geographical introduction to disasters. Longman Publish Group, London

    Google Scholar 

  • Huang C (2009) Integration degree of risk in terms of scene and application. Stoch Environ Res Risk Assess 23(4):473–484

    Article  Google Scholar 

  • Huang J, Ho M, Du P (2011a) Assessment of temporal and spatial variation of coastal water quality and source identification along Macau peninsula. Stoch Environ Res Risk Assess 25:353–361

    Article  Google Scholar 

  • Huang J, Liu Y, Ma L (2011b) Assessment of regional vulnerability to natural hazards in China using a DEA model. Int J Disaster Risk Sci 2(2):41–48

    Article  Google Scholar 

  • Kasperson JX, Kasperson RE, Turner BL, Schiller A, Hsieh WH (2003) Vulnerability to global environmental change. In: Diekmann A, Dietz T, Jaeger C, Rosa ES (eds) The human dimensions of global environmental change. MIT Press, Cambridge

    Google Scholar 

  • Levy JK (2005) Multiple criteria decision making and decision support systems for flood risk management. Stoch Environ Res Risk Assess 19:438–447

    Article  Google Scholar 

  • Levy JK, Hall J (2005) Advances in flood risk management under uncertainty. Stoch Environ Res Risk Assess 19:375–377

    Article  Google Scholar 

  • Liu B (2011) Multi-hazard risk assessment in the Yangtze River delta region: a case study on human life. Master thesis, Beijing Normal University (in Chinese)

  • Nason GP (2001) Robust projection indices. J Roy Stat Soc B 63(3):551–567

    Article  Google Scholar 

  • Opricovic S (2007) A fuzzy compromise solution for multicriteria problems. Int J Uncertain, Fuzziness Knowl-Based Syst 15(3):363–380

    Article  Google Scholar 

  • Philipp ST (2006) The spatial effects and management of natural and technological hazards in Europe. ESPON 1(3):1

    Google Scholar 

  • Puente S (1999) Social vulnerability to disaster in Mexico City. In: Mitchell JK (eds) Crucibles of hazard: mega-cities and disasters in transition. United Nations University Press, Tokyo, pp 295–334

  • Roy DC, Blaschke T (2011) A grid-based approach for spatial vulnerability assessment to floods: a case study on the coastal area of Bangladesh. GI4DM conference, Antalya

  • Rygel L, O’Sullivan D, Yarnal B (2006) A method for constructing a social vulnerability index: an application to hurricane storm surges in a developed country. Mitig Adapt Strat Glob Change 11(3):741–764

    Article  Google Scholar 

  • Saaty TL (1980) Analytical hierarch process. McGraw Hill, New York

    Google Scholar 

  • Sarkar A, Vulimiri A, Bose S, Paul S, Ray SS (2008) Unsupervised hyperspectral image analysis with projection pursuit and MRF segmentation approach. 2008 International Conference on Artificial Intelligence and Pattern Recognition (AIPR-08), pp 120–127

  • Thomas V (2011) It is time to factor natural disasters into macroeconomic scenarios. Econ Premise 52:1–4

    Google Scholar 

  • Turner BL, Matsond PA, McCarthy JJ, Corell RW, Christensen L, Eckley N, Hovelsrud-Brodah GK, Kasperson JX, Kasperson RE, Luers A, Martello ML, Mathiesen S, Naylor R, Polsky C, Pulsipher A, Schiller A, Selin H, Tyler N (2003) Illustrating the coupled human-environment system for vulnerability analysis: three case studies. PNAS 100(14):8080–8085

    Article  CAS  Google Scholar 

  • Wei Y, Fan Y, Lu C, Tsai H (2004) The assessment of vulnerability to natural disasters in China by using the DEA method. Environ Impact Assess Rev 24(4):427–439

    Article  Google Scholar 

  • Wisner B, Blaikie P, Cannon T, Davis I (2004) At risk: natural hazards, people’s vulnerability, and disasters. Routledge, London

    Google Scholar 

  • Zeng J, Zhu Z, Zhang J, Ouyang T, Qiu S, Zou Y, Zeng T (2012) Social vulnerability assessment of natural hazards on county-scale using high spatial resolution satellite imagery: a case study in the Luogang district of Guangzhou. South China. Environ Earth Sci 65(1):173–182

    Article  Google Scholar 

Download references

Acknowledgments

This study was supported by the National Natural Science Foundation of China (Grant no. 41201547), National Basic Research Program of China (973 Program) (Grant no. 2011CB707103), Programme of Introducing Talents of Discipline to Universities (Grant no. B08008), and Key Project in the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (Grant no. 2008BAK50B07). Special thanks to the reviewers and the editors for their critical comments that greatly helped in improving the quality of this paper. The authors greatly appreciate Dr. Ying Li for her help in improving the quality of the language.

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Authors and Affiliations

  1. State Key Laboratory of Pollution Control & Resource Re-use, School of the Environment, Nanjing University, Nanjing, 210093, China

    Yi Ge, Xin Qian & Xin Zhou

  2. School of Transportation, Southeast University, Nanjing, 210018, China

    Wen Dou

  3. College of Architecture & Urban Planning, Shenzhen University, Shenzhen, 518060, China

    Zhihui Gu

  4. Department of Geography, Social Science Center, The University of Western Ontario, 1151 Richmond Street, London, ON, N6A 5C2, Canada

    Jinfei Wang

  5. Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing, 100875, China

    Wei Xu, Peijun Shi & Xiaodong Ming

  6. Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing, 100875, China

    Wei Xu, Peijun Shi & Xiaodong Ming

  7. Information Center of Ministry of Science & Technology, Beijing, 100862, China

    Yuan Chen

Authors
  1. Yi Ge
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  2. Wen Dou
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  3. Zhihui Gu
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  4. Xin Qian
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  5. Jinfei Wang
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  6. Wei Xu
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  7. Peijun Shi
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  8. Xiaodong Ming
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  9. Xin Zhou
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  10. Yuan Chen
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Correspondence to Wei Xu.

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Ge, Y., Dou, W., Gu, Z. et al. Assessment of social vulnerability to natural hazards in the Yangtze River Delta, China. Stoch Environ Res Risk Assess 27, 1899–1908 (2013). https://doi.org/10.1007/s00477-013-0725-y

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  • DOI: https://doi.org/10.1007/s00477-013-0725-y

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