Skip to main content
SpringerLink
Log in

Urban Vulnerability Assessment: Towards a Cross-Scale Spatial Multi-criteria Approach

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10962))

Included in the following conference series:

Abstract

This paper analyses the issue of urban vulnerability assessment, aiming to identify appropriate strategies to mitigate the impacts of climate change, through decision-making processes that are attentive to the spatial, territorial and geographical scale. In complex decision-making problems, the spatial assessment of homogeneous vulnerability classes can become a useful support for translating the value of vulnerability into intervention priorities and enabling the selection of appropriate intervention alternatives. Urban vulnerability is a complex phenomenon requiring significant and effective indicators that allow an adequate assessment both in quantitative and qualitative terms.

Among the different multidimensional approaches present in the literature, as part of the METROPOLIS (Metodologie E Tecnologie integRate e sOstenibili Per l’adattamentO e La sicurezza deI Sistemi urbani) research project, developed by the local unit of the Department of Architecture, University of Naples Federico II, the multi-criteria and multi-group analysis method TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) was applied; this method is particularly suitable in complex decisional contexts, such as the level of vulnerability of a territory, where the kind of information relative to the performances to be evaluated presents considerable levels of uncertainty. The integration of the TOPSIS method in the GIS (Geographic Information System) makes it possible to test the opportunities of an integrated and cross-scale evaluation model, by structuring a Spatial Decision Support System (SDSS) applied to the case study of Naples, in the South of Italy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. UNEP: Cities and Urban Vulnerability in the Context of Urban Environmental Management. A Concept Paper (2007). https://www.unisdr.org/files/5453_092UNE.pdf

  2. IPCC: Climate Change and Biodiversity. IPCC, Geneva, Switzerland (2002). Core Writing Team, Gitai, H., Suárez, A., Watson, R.T., Dokken, D.J. (eds.)

    Google Scholar 

  3. McGeary, M.G.H., Lynn, L.E.: Urban Change and Poverty. National Academy Press, Washington, D.C. (1988)

    Google Scholar 

  4. Perchinunno, P., Rotondo, F., Torre, C.M.: A multivariate fuzzy analysis for the regeneration of urban poverty areas. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2008. LNCS, vol. 5072, pp. 137–152. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69839-5_11

    Chapter  Google Scholar 

  5. IPCC: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland (2014). Core Writing Team, Pachauri, R.K., Meyer, L.A. (eds.)

    Google Scholar 

  6. Füssel, H.M., Jol, A.: Climate change, impacts and vulnerability in Europe 2012. An indicator-based report. European Environment Agency (EEA) Report, 12, EEA, Copenhagen (2012)

    Google Scholar 

  7. IPCC: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge (2007). Core Writing Team, Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E. (eds.)

    Google Scholar 

  8. Bernstein, L.B.P., Canziani, O.: Intergovernmental panel on climate change. Fourth Assessment Report. Climate change 2007, Synthesis Report (2007)

    Google Scholar 

  9. Swart, R., Fons, J., Geertsema, W., van Hove, B., Gregor, M., Havranek, M., Peltonen, L.: Urban vulnerability indicators: a joint report of ETC-CCA and ETC-SIA. ETC-CCA and ETC-SIA Technical report 1/2012 (2012)

    Google Scholar 

  10. Chung, E.S., Lee, K.S.: Identification of spatial ranking of hydrological vulnerability using multi-criteria decision making techniques: case study of Korea. Water Resour. Manag. 23(12), 2395–2416 (2009)

    Article  Google Scholar 

  11. Jun, K.S., Chung, E.S., Kim, Y.G., Kim, Y.: A fuzzy multi-criteria approach to flood risk vulnerability in South Korea by considering climate change impacts. Expert Syst. Appl. 40(4), 1003–1013 (2013)

    Article  Google Scholar 

  12. Lee, G., Jun, K.S., Chung, E.S.: Integrated multi-criteria flood vulnerability approach using fuzzy TOPSIS and Delphi technique. Nat. Hazards Earth Syst. Sci. 13(5), 1293–1312 (2013)

    Article  Google Scholar 

  13. Kim, Y., Chung, E.S.: Assessing climate change vulnerability with group multi-criteria decision making approaches. Clim. Chang. 121(2), 301–315 (2013)

    Article  MathSciNet  Google Scholar 

  14. Kubal, C., Haase, D., Meyer, V., Scheuer, S.: Integrated urban flood risk assessment–adapting a multicriteria approach to a city. Nat. Hazards Earth Syst. Sci. 9(6), 1881–1895 (2009)

    Article  Google Scholar 

  15. Hinkel, J.: “Indicators of vulnerability and adaptive capacity”: towards a clarification of the science–policy interface. Global Environ. Chang. 21(1), 198–208 (2011)

    Article  Google Scholar 

  16. Adger, W.N.: Vulnerability. Global Environ. Chang. 16(3), 268–281 (2006)

    Article  Google Scholar 

  17. Moss, R.H., Brenkert, A.L., Malone, E.L.: Vulnerability to climate change: a quantitative approach, pp. 155–167. Pacific Northwest National Laboratory (PNNL-SA-33642). Prepared for the US Department of Energy (2001)

    Google Scholar 

  18. O’Brien, K., Leichenkob, R., Kelkarc, U., Venemad, H., Aandahla, G., Tompkinsa, H., Javedc, A., Bhadwalc, S., Bargd, S., Nygaarda, L., Westa, J.: Mapping vulnerability to multiple stressors: climate change and globalization in India. Global Environ. Chang. 14(4), 303–313 (2004)

    Article  Google Scholar 

  19. Balena, P., Sannicandro, V., Torre, C.M.: Spatial multicrierial evaluation of soil consumption as a tool for SEA. In: Murgante, B., et al. (eds.) ICCSA 2014. LNCS, vol. 8581, pp. 446–458. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09150-1_32

    Chapter  Google Scholar 

  20. Ishizaka, A., Nemery, P.: Multi-criteria Decision Analysis: Methods and Software. Wiley, Hoboken (2013)

    Book  Google Scholar 

  21. Hwang, C.L., Yoon, K.: Multiple Attribute Decision Making Methods and Applications. Springer, Heidelberg (1981). https://doi.org/10.1007/978-3-642-48318-9

    Book  MATH  Google Scholar 

  22. Huang, I.B., Keisler, J., Linkov, I.: Multi-criteria decision analysis in environmental science: ten years of applications and trends. Sci. Total Environ. 409, 3578–3594 (2011)

    Article  Google Scholar 

  23. Assari, A., Mahesh, T., Assari, E.: Role of public participation in sustainability of historical city: usage of TOPSIS method. Indian J. Sci. Technol. 5(3), 2289–2294 (2012)

    Google Scholar 

  24. Hung, C.C., Chen, L.H.: A fuzzy TOPSIS decision making model with entropy weight under intuitionistic fuzzy environment. In: Proceedings of the International Multi-Conference of Engineers and Computer Scientists IMECS, Hong Kong (2009)

    Google Scholar 

  25. Roszkowska, E.: Multi-criteria decision making models by applying the topsis method to crisp and interval data. Mult. Criteria Decis. Mak. 6, 200–230 (2011)

    Google Scholar 

  26. Eicher, C.L., Brewer, C.A.: Dasymetric mapping and areal interpolation: implementation and evaluation. Cartogr. Geogr. Inf. Sci. 28(2), 125–138 (2001)

    Article  Google Scholar 

  27. Sleeter, R.: Dasymetric mapping techniques for the San Francisco Bay region, California. In: Proceedings of the Urban and Regional Information Systems Association, Annual Conference, Reno, Nevada, 7–10 November 2004 (2004)

    Google Scholar 

  28. Mennis, J.: Generating surface models of population using dasymetric mapping. Prof. Geogr. 55(1), 31–42 (2003)

    Google Scholar 

  29. O’Sullivan, D., Unwin, D.: Geographic Information Analysis. Wiley, Hoboken (2014)

    Google Scholar 

  30. Maantay, J.A., Maroko, A.R., Herrmann, C.: Mapping population distribution in the urban environment: the cadastral-based expert dasymetric system (CEDS). Cartogr. Geogr. Inf. Sci. 34(2), 77–102 (2007)

    Article  Google Scholar 

  31. Holloway, S.R., Schumacher, J., Redmond, R.L.: People and place: dasymetric mapping using arc/info. Cartographic Design Using ArcView and Arc/Info, Wildlife Spatial Analysis Lab, University of Montana, Missoula (1997)

    Google Scholar 

  32. Chu, T.C.: Facility location selection using fuzzy TOPSIS under group decisions. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(06), 687–701 (2002)

    Article  MathSciNet  Google Scholar 

  33. Shih, H.S., Shyur, H.J., Lee, E.S.: An extension of TOPSIS for group decision making. Math. Comput. Model. 45(7), 801–813 (2007)

    Article  Google Scholar 

  34. Saari, D.G.: The Bordà dictionary. Soc. Choice Welf. 7(4), 279–317 (1990)

    Article  MathSciNet  Google Scholar 

  35. Amato, F., Pontrandolfi, P., Murgante, B.: Supporting planning activities with the assessment and the prediction of urban sprawl using spatio-temporal analysis. Ecol. Inform. 30, 365–378 (2015)

    Article  Google Scholar 

  36. Fusco, G.L., Cerreta, M., De Toro, P.: Integrated assessment for sustainable choices. Scienze Regionali 13(1), 111–142 (2014)

    Google Scholar 

  37. Mokhtarian, M.N., Hadi-Vencheh, A.: A new fuzzy TOPSIS method based on left and right scores: an application for determining an industrial zone for dairy products factory. Appl. Soft Comput. 12(8), 2496–2505 (2012)

    Article  Google Scholar 

  38. Cerreta, M., Panaro, S.: From perceived values to shared values: a multi-stakeholder spatial decision analysis (M-SSDA) for resilient landscapes. Sustainability 9, 1–20 (2017)

    Google Scholar 

  39. Cerreta, M., Inglese, P., Malangone, V., Panaro, S.: Complex values-based approach for multidimensional evaluation of landscape. In: Murgante, B., et al. (eds.) ICCSA 2014. LNCS, vol. 8581, pp. 382–397. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09150-1_28

    Chapter  Google Scholar 

  40. Cerreta, M., Poli, G.: Landscape services assessment: a hybrid multi-criteria spatial decision support system (MC-SDSS). Sustainability 9, 1–18 (2017)

    Google Scholar 

  41. Attardi, R., Cerreta, M., Sannicandro, V., Torre, C.M.: Non-compensatory composite indicators for the evaluation of urban planning policy: the land-use policy efficiency index (LUPEI). Eur. J. Oper. Res. 264, 491–507 (2017)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Architecture, University of Naples Federico II, via Toledo 402, 80134, Naples, Italy

    Maria Cerreta, Roberta Mele & Giuliano Poli

Authors
  1. Maria Cerreta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roberta Mele
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giuliano Poli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maria Cerreta .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cerreta, M., Mele, R., Poli, G. (2018). Urban Vulnerability Assessment: Towards a Cross-Scale Spatial Multi-criteria Approach. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10962. Springer, Cham. https://doi.org/10.1007/978-3-319-95168-3_34

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95168-3_34

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95167-6

  • Online ISBN: 978-3-319-95168-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation