IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v70y2014i1p1-22.html
   My bibliography  Save this article

Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius

Author

Listed:
  • Iain Willis
  • Maurizio Gibin
  • Joana Barros
  • Richard Webber

Abstract

Mt Vesuvius is regarded as one of the most deadly volcanoes on earth. With over 1 million people living on its flanks and in its periphery, there is little doubt that an eruption of sub-Plinian magnitude would be catastrophic to the livelihood and well being of contemporary Neopolitans. Such a large scale eruption would have wide ranging and differential effects on the surrounding population. Whereas previous studies of social vulnerability have focused on individual demographic factors (such as age, income or ethnicity), this research proposes the application of a general neighbourhood classification system to assess natural hazard vulnerability. In this study, Experian’s Mosaic Italy is used to classify and delineate the most vulnerable neighbourhood types around the province of Naples. Among the neighbourhoods considered most at risk, those areas with high proportions of elderly and low income families are deemed particularly vulnerable. With current evacuation plans deemed outdated and poorly communicated to the locals Rolandi ( 2010 ), Barberi et al. ( 2008 ), this methodology could prove to be a useful input to both town planners and civil protection agencies. A range of statistical measures and geophysical risk boundaries are employed here to assess the different areas of human resilience. Copyright Springer Science+Business Media B.V. 2014

Suggested Citation

  • Iain Willis & Maurizio Gibin & Joana Barros & Richard Webber, 2014. "Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 1-22, January.
    • Handle: RePEc:spr:nathaz:v:70:y:2014:i:1:p:1-22
    DOI: 10.1007/s11069-010-9648-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-010-9648-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-010-9648-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mattia Amadio & Jaroslav Mysiak & Sepehr Marzi, 2019. "Mapping Socioeconomic Exposure for Flood Risk Assessment in Italy," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 829-845, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    2. Modalsli, Jørgen, 2011. "Inequality and growth in the very long run: inferring inequality from data on social groups," Memorandum 11/2011, Oslo University, Department of Economics.
    3. Stephen Davies & Peter L. Ormosi, 2014. "The economic impact of cartels and anti-cartel enforcement," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2013-07v2, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    4. Zhu, Yongjun & Yan, Erjia, 2017. "Examining academic ranking and inequality in library and information science through faculty hiring networks," Journal of Informetrics, Elsevier, vol. 11(2), pages 641-654.
    5. Csörgö, Miklós & Zitikis, Ricardas, 1997. "On the rate of strong consistency of Lorenz curves," Statistics & Probability Letters, Elsevier, vol. 34(2), pages 113-121, June.
    6. Johan Fellman, 2021. "Empirical Analyses of Income: Finland (2009) and Australia (1967-1968)," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 10(1), pages 1-3.
    7. WANG, Zuxiang & SMYTH, Russell & NG, Yew-Kwang, 2009. "A new ordered family of Lorenz curves with an application to measuring income inequality and poverty in rural China," China Economic Review, Elsevier, vol. 20(2), pages 218-235, June.
    8. Ugo Panizza, 1999. "Desigualdad del ingreso y crecimiento económico: elementos de juicio de datos de USA," Research Department Publications 4179, Inter-American Development Bank, Research Department.
    9. James B. Mcdonald & Jeff Sorensen & Patrick A. Turley, 2013. "Skewness And Kurtosis Properties Of Income Distribution Models," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(2), pages 360-374, June.
    10. Anthony B Aktinson, 2015. "Top incomes in East Africa before and after independence," Working Papers halshs-02654566, HAL.
    11. Huimin Xu & Shougeng Hu & Xi Li, 2023. "Urban Distribution and Evolution of the Yangtze River Economic Belt from the Perspectives of Urban Area and Night-Time Light," Land, MDPI, vol. 12(2), pages 1-21, January.
    12. Yves Tillé, 2016. "The legacy of Corrado Gini in survey sampling and inequality theory," METRON, Springer;Sapienza Università di Roma, vol. 74(2), pages 167-176, August.
    13. Fontanari, Andrea & Cirillo, Pasquale & Oosterlee, Cornelis W., 2018. "From Concentration Profiles to Concentration Maps. New tools for the study of loss distributions," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 13-29.
    14. Daranrat Jaitiang & Wen-Chi Huang & Shang-Ho Yang, 2021. "Does Income Inequality Exist among Urban Farmers? A Demonstration of Lorenz Curves from Northern Thailand," Sustainability, MDPI, vol. 13(9), pages 1-16, May.
    15. Sung Y. Park & Anil K. Bera, 2018. "Information theoretic approaches to income density estimation with an application to the U.S. income data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(4), pages 461-486, December.
    16. Kazuhiko Kakamu, 2022. "Bayesian analysis of mixtures of lognormal distribution with an unknown number of components from grouped data," Papers 2210.05115, arXiv.org, revised Sep 2023.
    17. David E. Altig & Charles T. Carlstrom, 1995. "Marginal tax rates and income inequality: a quantitative-theoretic analysis," Working Papers (Old Series) 9508, Federal Reserve Bank of Cleveland.
    18. Albu, Lucian Liviu, 2012. "The Convergence Process in the EU Estimated by Gini Coefficients," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-16, December.
    19. Jørgen Modalsli, 2015. "Inequality in the very long run: inferring inequality from data on social groups," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(2), pages 225-247, June.
    20. Korb, Penelope J. & Blank, Steven C. & Erickson, Kenneth W., 2004. "Profit Patterns In The U.S. And The West, 1992 And 1997: What County-Level Data Reveal," 2004 Annual Meeting, June 30-July 2, 2004, Honolulu, Hawaii 36253, Western Agricultural Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:70:y:2014:i:1:p:1-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.