A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

Pedro Pinto Santos; José Luís Zêzere; Susana Pereira; Jorge Rocha; Alexandre Oliveira Tavares

doi:10.1007/s13753-022-00455-w

Volume 13 Issue 6

Feb. 2023

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Pedro Pinto Santos, José Luís Zêzere, Susana Pereira, Jorge Rocha, Alexandre Oliveira Tavares. A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal[J]. International Journal of Disaster Risk Science, 2022, 13(6): 842-861. doi: 10.1007/s13753-022-00455-w

Citation:

Pedro Pinto Santos, José Luís Zêzere, Susana Pereira, Jorge Rocha, Alexandre Oliveira Tavares. A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal[J]. International Journal of Disaster Risk Science, 2022, 13(6): 842-861. doi: 10.1007/s13753-022-00455-w

Citation:

Pedro Pinto Santos, José Luís Zêzere, Susana Pereira, Jorge Rocha, Alexandre Oliveira Tavares. A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal[J]. International Journal of Disaster Risk Science, 2022, 13(6): 842-861. doi: 10.1007/s13753-022-00455-w

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A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

doi: 10.1007/s13753-022-00455-w

1. Centre for Geographical Studies, Institute of Geography and Spatial Planning, TERRA, University of Lisbon(CEG-IGOT-ULisboa), 1600-276, Lisboa, LA, Portugal;
2. Centre for Social Studies, Earth Science Department, Science and Technology Faculty, University of Coimbra(CES/DCT-FCT-UCoimbra), 3000-995, Coimbra, Portugal

Funds:

This work was funded by FCT (Fundaç

ncia e Tecnologia / Portuguese Foundation for Science and Technology), through the projects “BeSafeSlide—Landslide early warning soft technology prototype to improve community resilience and adaptation to environmental change” (PTDC/GES-AMB/30052/2017) and “MIT-RSC—Multi-risk interactions towards resilient and sustainable cities” (MIT-EXPL/CS/0018/2019). Jorge Rocha was financed through FCT, within the framework of the project “TRIAD—Health risk and social vulnerability to arboviral diseases in mainland Portugal” (PTDC/GES-OUT/30210/2017). This work was also partially developed within the framework of the RISKCOAST project (Ref: SOE3/P4/E0868) funded by the Interreg SUDOE Program (3rd Call for proposals). Pedro Pinto Santos was financed by FCT, within the framework of the contract CEEIND/00268/2017, and by the Research Unit UID/GEO/00295/2020.

o para a Ciê

Received Date: 2022-11-09
Accepted Date: 2022-11-09

Available Online: 2023-02-09

Publish Date: 2022-11-28

Abstract

Abstract

Social vulnerability, as one of the risk components, partially explains the magnitude of the impacts observed after a disaster. In this study, a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal, at the civil parish level, for three census frames. The first challenging step consisted of the selection of meaningful and consistent variables over time. Data were normalized using the Adjusted Mazziotta-Pareto Index (AMPI) to obtain comparable adimensional-normalized values. A joint principal component analysis (PCA) was applied, resulting in a robust set of variables, interpretable from the point of view of their self-grouping around vulnerability drivers. A separate PCA for each census was also conducted, which proved to be useful in analyzing changes in the composition and type of drivers, although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011. A general improvement in social vulnerability was observed for Portugal. The two main drivers are the economic condition (PC1), and aging and depopulation (PC2). The remaining drivers highlighted are uprooting and internal mobility, and daily commuting. Census data proved their value in the territorial, social, and demographic characterization of the country, to support medium- and long-term disaster risk reduction measures.
- AMPI normalization,
- Portugal,
- Social vulnerability,
- Spatiotemporal changes

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References(50)

References

Adger, W.N., N. Brooks, G. Bentham, M. Agnew, and S. Eriksen. 2004. New indicators of vulnerability and adaptive capacity. Tyndall Centre for Climate Change Research, Technical report 7. Norwich, UK:University of East Anglia. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.112.2300&rep=rep1&type=pdf. Accessed 16 Jun 2020.

Alexander, D. 2012. Models of social vulnerability to disasters. RCCS Annual Review 4:22-40.

Apotsos, A. 2019. Mapping relative social vulnerability in six mostly urban municipalities in South Africa. Applied Geography 105:86-101.

Barros, J.L., A.O. Tavares, A. Santos, and A. Fonte. 2015. Territorial vulnerability assessment supporting risk managing coastal areas due to tsunami impact. Water 7(9):4971-4998.

Bergstrand, K., B. Mayer, B. Brumback, and Y. Zhang. 2015. Assessing the relationship between social vulnerability and community resilience to hazards. Social Indicators Research 122(2):391-409.

Bigi, V., E. Comino, M. Fontana, A. Pezzoli, and M. Rosso. 2021. Flood vulnerability analysis in urban context:A socioeconomic sub-indicators overview. Climate 9(1):Article 12.

Bronfman, N.C., P.B. Repetto, N. Guerrero, J.V. Castañeda, and P.C. Cisternas. 2021. Temporal evolution in social vulnerability to natural hazards in Chile. Natural Hazards 107(2):1757-1784.

Chen, W., S.L. Cutter, C.T. Emrich, and P. Shi. 2013. Measuring social vulnerability to natural hazards in the Yangtze River Delta Region, China. International Journal of Disaster Risk Science 4(4):169-181.

Comfrey, A.L., and H.B. Lee. 1992. A first course in factor analysis. Hillsdale, NJ:Lawrence Erlbaum Associates.

Contreras, D., A. Chamorro, and S. Wilkinson. 2020. The spatial dimension in the assessment of urban socio-economic vulnerability related to geohazards. Natural Hazards and Earth System Sciences 20(6):1663-1687.

Cutter, S.L. 2017. The forgotten casualties redux:Women, children, and disaster risk. Global Environmental Change 42:117-121.

Cutter, S.L., and C. Finch. 2008. Temporal and spatial changes in social vulnerability to natural hazards. Proceedings of the National Academy of Sciences 105(7):2301-2306.

Cutter, S.L., B.J. Boruff, and W.L. Shirley. 2003. Social vulnerability to environmental hazards. Social Science Quarterly 84(2):242-261.

de Loyola Hummell, B.M., S.L. Cutter, and C.T. Emrich. 2016. Social vulnerability to natural hazards in Brazil. International Journal of Disaster Risk Science 7(2):111-122.

DGT (Direção Geral do Território, Territory General Directorate). 2019. National Spatial Planning Policy Program-Alteration diagnosis (Programa Nacional Da Política de Ordenamento Do Território-Alteração Diagnóstico). Lisbon, Portugal:DGT (in Portuguese).

Dintwa, K.F., G. Letamo, and K. Navaneetham. 2019. Measuring social vulnerability to natural hazards at the district level in Botswana. Jamba:Journal of Disaster Risk Studies 11(1):1-11.

Eidsvig, U.M.K., A. McLean, B.V. Vangelsten, B. Kalsnes, R.L. Ciurean, S. Argyroudis, M.G. Winter, and O.C. Mavrouli et al. 2014. Assessment of socioeconomic vulnerability to landslides using an indicator-based approach:Methodology and case sudies. Bulletin of Engineering Geology and the Environment 73(2):307-324.

EU (European Union). 2020. Science for disaster risk management 2020:Acting today, protecting tomorrow-EUR 30183, ed. A. Casajus-Valles, M. Marin Ferrer, K. Poljanšek, and I. Clark. Luxembourg:Publications Office of the European Union.

Fatemi, F., A. Ardalan, B. Aguirre, N. Mansouri, and I. Mohammadfam. 2017. Social vulnerability indicators in disasters:Findings from a systematic review. International Journal of Disaster Risk Reduction 22:219-227.

Fekete, A. 2010. Assessment of social vulnerability to river floods in Germany. PhD dissertation. Bonn, Germany:University of Bonn. http://collections.unu.edu/view/UNU:1978. Accessed 14 Jun 2020.

Fekete, A. 2019a. Social vulnerability (re-)assessment in context to natural hazards:Review of the usefulness of the spatial indicator approach and investigations of validation demands. International Journal of Disaster Risk Science 10(2):220-232.

Fekete, A. 2019b. Social vulnerability change assessment:Monitoring longitudinal demographic indicators of disaster risk in Germany from 2005 to 2015. Natural Hazards 95(3):585-614.

Finch, C., C.T. Emrich, and S.L. Cutter. 2010. Disaster disparities and differential recovery in New Orleans. Population and Environment 31(4):179-202.

Frigerio, I., F. Carnelli, M. Cabinio, and M. De Amicis. 2018. Spatiotemporal pattern of social vulnerability in Italy. International Journal of Disaster Risk Science 9(2):249-262.

Frigerio, I., S. Ventura, D. Strigaro, M. Mattavelli, M. De Amicis, S. Mugnano, and M. Boffi. 2016. A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy. Applied Geography 74:12-22.

Guillard-Gonçalves, C., and J.L. Zêzere. 2018. Combining social vulnerability and physical vulnerability to analyse landslide risk at the municipal scale. Geosciences 8(8):Article 294.

Guillard-Goncąlves, C., S.L. Cutter, C.T. Emrich, and J.L. Zêzere. 2015. Application of Social Vulnerability Index (SoVI) and delineation of natural risk zones in Greater Lisbon, Portugal. Journal of Risk Research 18(5):651-674.

Hofflinger, A., M.A. Somos-Valenzuela, and A. Vallejos-Romero. 2019. Response time to flood events using a Social Vulnerability Index (ReTSVI). Natural Hazards and Earth System Sciences 19(1):251-267.

Huynh, L.T.M., and L.C. Stringer. 2018. Multi-scale assessment of social vulnerability to climate change:An empirical study in coastal Vietnam. Climate Risk Management 20:165-180.

INE (Instituto Nacional de Estatística/National Statistics Institute). 2011. Population census-2011. Lisbon, Portugal:INE.

Maiti, S., S.K. Jha, S. Garai, A. Nag, A.K. Bera, V. Paul, R.C. Upadhaya, and S.M. Deb. 2017. An assessment of social vulnerability to climate change among the districts of Arunachal Pradesh, India. Ecological Indicators 77:105-113.

Marulanda-Fraume, M.C., O.D. Cardona, P. Marulanda-Fraume, M.L. Carreño, and A.H. Barbat. 2020. Evaluating risk from a holistic perspective to improve resilience:The United Nations evaluation at global level. Safety Science 127:Article 104739.

Mazziotta, M., and A. Pareto. 2016. On a generalized non-compensatory composite index for measuring socio-economic phenomena. Social Indicators Research 127(3):983-1003.

Mazziotta, M., and A. Pareto. 2018. Measuring well-being over time:The Adjusted Mazziotta-Pareto Index versus other non-compensatory indices. Social Indicators Research 136(3):967-976.

Mazziotta, M., and A. Pareto. 2021. Data normalization for aggregating time series:The constrained min-max method. RIEDS-The Italian Journal of Economic, Demographic and Statistical Studies 75(4):86-96.

Mendes, J.M. 2009. Social vulnerability indexes as planning tools:Beyond the preparedness paradigm. Journal of Risk Research 12(1):43-58.

Mendes, J.M., A.O. Tavares, and P.P. Santos. 2019. Social vulnerability and local level assessments:A new approach for planning. International Journal of Disaster Resilience in the Built Environment 11(1):15-43.

OECD (Organisation for Economic Co-operation and Development). 2008. Handbook on constructing composite indicators. Methodology and user guide. Paris:OECD. https://www.oecd.org/els/soc/handbookonconstructingcompositeindicatorsmethodologyanduserguide.htm. Accessed 3 May 2020.

Ogie, R.I., and B. Pradhan. 2019. Natural hazards and social vulnerability of place:The strength-based approach applied to Wollongong, Australia. International Journal of Disaster Risk Science 10(3):404-420.

Park, G., and Z. Xu. 2020. Spatial and temporal dynamics of social vulnerability in the United States from 1970 to 2010:A county trajectory analysis. International Journal of Applied Geospatial Research 11(1):Article 19.

Roder, G., G. Sofia, Z. Wu, and P. Tarolli. 2017. Assessment of social vulnerability to floods in the floodplain of Northern Italy. Weather, Climate, and Society 9(4):717-737.

Rufat, S., E. Tate, C.G. Burton, and A.S. Maroof. 2015. Social vulnerability to floods:Review of case studies and implications for measurement. International Journal of Disaster Risk Reduction 14:470-486.

Spiekermann, R., S. Kienberger, J. Norton, F. Briones, and J. Weichselgartner. 2015. The disaster-knowledge matrix-Reframing and evaluating the knowledge challenges in disaster risk reduction. International Journal of Disaster Risk Reduction 13:96-108.

Tavares, A.O., J.L. Barros, J.M. Mendes, P.P. Santos, and S. Pereira. 2018. Decennial comparison of changes in social vulnerability:A municipal analysis in support of risk management. International Journal of Disaster Risk Reduction 31:679-690.

Tavares, A.O., J.M. Mendes, and E. Basto. 2011. Perception of natural and technological risks, institutional confidence and emergency preparedness:The case of mainland Portugal (Percepção Dos Riscos Naturais e Tecnológicos, Confiança Institucional e Preparação Para Situações de Emergência:O Caso de Portugal Continental). Revista Crítica de Ciências Sociais 93:167-193(in Portuguese).

UNDP (United Nations Development Programme). 2017. Social vulnerability assessment tools for climate change and DRR programming. New York:United Nations Development Programme. https://www.adaptation-undp.org/sites/default/files/resources/social_vulnerability05102017_0.pdf. Accessed 3 May 2020.

United Nations. 2016. Report of the open-ended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction (A/71/644). New York:United Nations.

Yoon, D.K. 2012. Assessment of social vulnerability to natural disasters:A comparative study. Natural Hazards 63(2):823-843.

Zebardast, E. 2013. Constructing a social vulnerability index to earthquake hazards using a hybrid factor analysis and analytic network process (F'ANP) model. Natural Hazards 65(3):1331-1359.

Zhou, Y., N. Li, W. Wu, J. Wu, and P. Shi. 2014. Local spatial and temporal factors influencing population and societal vulnerability to natural disasters. Risk Analysis 34(4):614-639.

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