Abstract
Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVID) was derived, and the global and local Moran’s I of the SVID were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVID values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.
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References
Adeagbo A, Daramola A, Carim-Sanni A, Akujobi C, Ukpong C (2016) Effects of natural disasters on social and economic well being: a study in Nigeria. Int J Disaster Risk Reduct 17:1–12. https://doi.org/10.1016/j.ijdrr.2016.03.006
Agovino M, Cerciello M, Gatto A (2018) Policy efficiency in the field of food sustainability. The adjusted food agriculture and nutrition index. J Environ Manage 218:220–233. https://doi.org/10.1016/j.jenvman.2018.04.058
Agrawala S, Conde C, Pulhin J, Pulwarty R, Smit B, Takahashi K, Parry ML, Canziani OF, Palutikof JP, Linden PJ Van Der, Hanson CE (2007) Assessment of adaptation practices, options, constraints and capacity. In: Parry M, Canziani O, Palutikof J, van der Linden P, Hanson C (eds) Climate change 2007. Impacts, adaptation and vulnerability: Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change, Climate ch. Cambridge University Press, Cambridge, pp 717–743
Alcantara E, Mantovani J, Rotta L, Park E, Rodrigues T, Carvalho F, Souza Filho C (2020) Investigating spatiotemporal patterns of the COVID-19 in Sao Paulo State. Brazil. https://doi.org/10.1101/2020.05.28.20115626
Anwaer M, Zhang X, Cao H (2013) Urbanization in Western China. Chin J Popul Resour Environ 11:79–86
Bjarnadottir S, Li Y, Stewart MG (2011) Social vulnerability index for coastal communities at risk to hurricane hazard and a changing climate. Nat Hazards 59:1055–1075. https://doi.org/10.1007/s11069-011-9817-5
Brooks N (2003) Vulnerability, risk and adaptation: a conceptual framework
Cardona OD, Van Aalst MK, Birkmann J, Fordham M, Mc Gregor G, Rosa P, Pulwarty RS, Schipper ELF, Sinh BT, Décamps H, Keim M, Davis I, Ebi KL, Lavell A, Mechler R, Murray V, Pelling M, Pohl J, Smith AO, Thomalla F (2012) Determinants of risk: exposure and vulnerability. Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change. Managing t. Cambridge University Press, New York, pp 65–108
Chen W, Cutter SL, Emrich CT, Shi P (2013) Measuring social vulnerability to natural hazards in the Yangtze River Delta region, China. Int J Disaster Risk Sci 4:169–181. https://doi.org/10.1007/s13753-013-0018-6
Collins SL, Carpenter SR, Swinton SM, Orenstein DE, Childers DL, Gragson TL, Grimm NB, Morgan GJ, Harlan SL, Kaye JP, Knapp AK, Kofinas GP, Magnuson JJ, McDowell WH, Melack JM, Ogden LA, Philip RG, Smith MD, Whitmer AC (2011) An integrated conceptual framework for long-term social-ecological research. Front Ecol Environ 9:351–357. https://doi.org/10.1890/100068
Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84:242–261. https://doi.org/10.1111/1540-6237.8402002
Foladare I (1969) A clarification of ‘“ascribed status”’ and ‘“achieved status”.’ Sociol Quart 10:53–61
Frankenberg E, Sikoki B, Sumantri C, Suriastini W, Thomas D (2013) Education. Vulnerab Resil Nat Disaster 18:16
Garschagen M, Romero-Lankao P (2015) Exploring the relationships between urbanization trends and climate change vulnerability. Clim Change 133:37–52. https://doi.org/10.1007/s10584-013-0812-6
Gatto A, Busato F (2019) Defining , measuring and ranking energy vulnerability Andrea Gatto and Francesco Busato CREATES Research Paper 2019–1
Ge Y, Dou W, Gu Z, Qian X (2013) Assessment of social vulnerability to natural hazards in the Yangtze River Delta. China. https://doi.org/10.1007/s00477-013-0725-y
Ge Y, Dou W, Liu N (2017a) Planning resilient and sustainable cities: Identifying and targeting social vulnerability to climate change. Sustain. https://doi.org/10.3390/su9081394
Ge Y, Yang G, Chen Y, Dou W (2019) Examining social vulnerability and inequality: A joint analysis through a connectivity lens in the urban agglomerations of China. Sustain. https://doi.org/10.3390/su11041042
Ge Y, Zhang H, Dou W, Chen W, Liu N, Wang Y, Shi Y, Rao W (2017b) Mapping social vulnerability to air pollution: a case study of the Yangtze River Delta Region. China Sustain 9:109. https://doi.org/10.3390/su9010109
Guillard-gonçalves C, Cutter SL, Emrich CT (2015) Application of Social Vulnerability Index (SoVI) and delineation of natural risk zones in Greater Lisbon, Portugal. J Risk Res 9877:1–24. https://doi.org/10.1080/13669877.2014.910689
Hession SL, Moore N (2011) A spatial regression analysis of the influence of topography on monthly rainfall in East Africa. Int J Climatol 31:1440–1456. https://doi.org/10.1002/joc.2174
Hinkel J (2011) “Indicators of vulnerability and adaptive capacity”: Towards a clarification of the science–policy interface. Glob Environ Chang 21:198–208. https://doi.org/10.1016/j.gloenvcha.2010.08.002
Holand IS, Lujala P (2012) Replicating and adapting an index of social vulnerability to a new context: a comparison study for Norway. Prof Geogr 65:120529141302005. https://doi.org/10.1080/00330124.2012.681509
Hou J, Lv J, Chen X, Yu S (2016) China’s regional social vulnerability to geological disasters : evaluation and spatial characteristics analysis. Nat Hazards 84:97–111. https://doi.org/10.1007/s11069-015-1931-3
IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation: a special report of working groups I and II of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Jones MC, Sibson R (1987) What is projection pursuit? J R Stat Soc Ser A 150:1–37
Jurgilevich A, Räsänen A, Groundstroem F, Juhola S (2017) A systematic review of dynamics in climate risk and vulnerability assessments. Environ Res Lett. https://doi.org/10.1088/1748-9326/aa5508
Kamal-chaoui L, Leman E, Rufei Z (2009) Urban Trends and Policy in China. OECD Reg Dev Work Pap 2009/1. OECD Publishing. https://doi.org/https://doi.org/10.1787/225205036417
Khazai B, Merz M, Schulz C, Borst D (2013) An integrated indicator framework for spatial assessment of industrial and social vulnerability to indirect disaster losses. Nat Hazards 67:145–167. https://doi.org/10.1007/s11069-013-0551-z
Kleinosky L, Yarnal B, Fisher A (2007) Vulnerability of Hampton Roads, Virginia to storm-surge flooding and sea-level rise. Nat Hazards 40:43–70
Li K, Wu S, Dai E, Xu Z (2012) Flood loss analysis and quantitative risk assessment in China. Nat Hazards 63:737–760
May CK (2019) Resilience, vulnerability, & transformation: exploring community adaptability in coastal North Carolina. Ocean Coast Manag 169:86–95. https://doi.org/10.1016/j.ocecoaman.2018.12.007
Nason GP (2001) Robust projection indices. J R Stat Soc Ser B Stat Methodol 63:551–567
Nguyen CV, Horne R, Fien J, Cheong F (2017) Assessment of social vulnerability to climate change at the local scale: development and application of a Social Vulnerability Index. Clim Change 143:355–370. https://doi.org/10.1007/s10584-017-2012-2
Pelling M (2003) The vulnerability of cities: natural disasters and social resilience earthscan. Sterling, VA, London
Pelling M, Mustafa D (2008) Vulnerability, disasters and poverty in desakota systems
Rajesh S, Jain S, Sharma P (2018) Inherent vulnerability assessment of rural households based on socio-economic indicators using categorical principal component analysis: a case study of Kimsar region, Uttarakhand. Ecol Indic 85:93–104. https://doi.org/10.1016/j.ecolind.2017.10.014
Romero Lankao P, Qin H (2011) Conceptualizing urban vulnerability to global climate and environmental change. Curr Opin Environ Sustain 3:142–149. https://doi.org/10.1016/j.cosust.2010.12.016
Roncancio DJ, Nardocci AC (2016) Social vulnerability to natural hazards in São Paulo, Brazil. Nat Hazards 84:1367–1383. https://doi.org/10.1007/s11069-016-2491-x
Ruibo H, Linna W (2013) Challenges and opportunities facing China’s urban development in the new Era. China Perspect 2013:15–27. https://doi.org/10.4000/chinaperspectives.6149
Spielman SE, Tuccillo J, Folch DC, Schweikert A, Davies R, Wood N, Tate E (2020) Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index. Nat Hazards 100:417–436. https://doi.org/10.1007/s11069-019-03820-z
Srivastava RK (2020) Urbanization-led neo risks and vulnerabilities: a new challenge
Su B, Huang J, Fischer T, Wang Y, Kundzewicz ZW, Zhai J (2018) Drought losses in China might double between the 1.5 °C and 2.0 °C warming. Proc Natl Acad Sci 2018:115
Sun Y, Hu X, Xie J (2020) Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England
Thomas K, Hardy RD, Lazrus H, Mendez M, Orlove B, Rivera-Collazo I, Roberts JT, Rockman M, Warner BP, Winthrop R (2019) Explaining differential vulnerability to climate change: A social science review. Wiley Interdiscip Rev Clim Chang 10:1–18. https://doi.org/10.1002/wcc.565
Turok I, McGranahan G (2013) Urbanization and economic growth: the arguments and evidence for Africa and Asia. Environ Urban 25:465–482. https://doi.org/10.1177/0956247813490908
Woetzel J, Henderson K, Krishnan M, Zhang HZ, Lam G (2020) Leading the battle against climate change: Actions for China. https://www.mckinsey.com/business-functions/sustainability/our-insights/leading-the-battle-against-climate-change-actions-for-china. Accessed 22 Oct 2020
Wu S, Liu L, Gao J, Wang W (2019) Integrate risk from climate change in china under global warming of 1.5 and 2.0 °C. Earth’s Futur 7:1307–1322. https://doi.org/10.1029/2019EF001194
Xiao Y, Song Y, Wu X (2018) How far has China’s urbanization gone? Sustain. https://doi.org/10.3390/su10082953
Xu J, Takahashi M (2020) Progressing vulnerability of the immigrants in an urbanizing village in coastal China. Environ Dev Sustain. https://doi.org/10.1007/s10668-020-00914-8
Yoon DK (2012) Assessment of social vulnerability to natural disasters: a comparative study. Nat Hazards 63:823–843. https://doi.org/10.1007/s11069-012-0189-2
Yu S, Lu H (2018) An integrated model of water resources optimization allocation based on projection pursuit model – Grey wolf optimization method in a transboundary river basin. J Hydrol 559:156–165. https://doi.org/10.1016/j.jhydrol.2018.02.033
Yu X, Xie J, Jiang R, Zuo G, Liang J (2020) Assessment of water resource carrying capacity based on the chicken swarm optimization-projection pursuit model. Arab J Geosci. https://doi.org/10.1007/s12517-019-5010-z
Zhong L, Li X, Law R, Sun S (2020) Developing sustainable urbanization index: case of China. Sustain 12:1–23. https://doi.org/10.3390/su12114585
Zhou Y, Li N, Wu W, Wu J, Shi P (2014) Local spatial and temporal factors influencing population and societal vulnerability to natural disasters. Risk Anal 34:614–639. https://doi.org/10.1111/risa.12193
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Many thanks to the reviewers and editors for their critical comments that greatly helped to improve the quality of this paper.
Funding
This research was funded by the National Natural Science Foundation of China (Grant Nos. 41571488, 41401382 and 41701186), and the Philosophy and Social Sciences Foundation in Jiangsu Province (Grant No. 17JDB010).
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Data curation, Yi Ge, Yi Chen and Ziyuan Zhang; Formal analysis, Yi Ge and Xiaotao Wang; Methodology, Wen Dou; Software, Wen Dou; Visualization, Wen Dou; Writing—original draft, Yi Ge.
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Ge, Y., Dou, W., Wang, X. et al. Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China. Nat Hazards 108, 2629–2651 (2021). https://doi.org/10.1007/s11069-021-04792-9
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DOI: https://doi.org/10.1007/s11069-021-04792-9