Skip to main content

Advertisement

SpringerLink
Log in

Spatial exposure aspects contributing to vulnerability and resilience assessments of urban critical infrastructure in a flood and blackout context

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Blackouts aggravate the situation during an extreme river-flood event by affecting residents and visitors of an urban area. But also rescue services, fire brigades and basic urban infrastructure such as hospitals have to operate under suboptimal conditions. This paper aims to demonstrate how affected people, critical infrastructure, such as electricity, roads and civil protection infrastructure are intertwined during a flood event, and how this can be analysed in a spatially explicit way. The city of Cologne (Germany) is used as a case study since it is river-flood prone and thousands of people had been affected in the floods in 1993 and 1995. Components of vulnerability and resilience assessments are selected with a focus of analysing exposure to floods, and five steps of analysis are demonstrated using a geographic information system. Data derived by airborne and spaceborne earth observation to capture flood extent and demographic data are combined with place-based information about location and distance of objects. The results illustrate that even fire brigade stations, hospitals and refugee shelters are within the flood scenario area. Methodologically, the paper shows how criticality of infrastructure can be analysed and how static vulnerability assessments can be improved by adding routing calculations. Fire brigades can use this information to improve planning on how to access hospitals and shelters under flooded road conditions.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

a Data source map, based on data from offenedaten-koeln.de, opendata.arcgis.com, geofabrik, city of Cologne. b Data source map, based on data from offenedaten-koeln.de, opendata.arcgis.com, geofabrik, city of Cologne. c Image source Statistical Yearbook of the City of Cologne 2015: 43. Legend shows share among all inhabitants in per cent

Fig. 3

a Data source map, based on data from offenedaten-koeln.de, opendata.arcgis.com, geofabrik. city of Cologne. b Image source Statistical Yearbook of the City of Cologne 2015: 104. Legend shows share among all inhabitants in per cent. c Image source Statistical Yearbook of the City of Cologne 2015: 168. Legend shows quota in per cent

Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Adger WN (2006) Vulnerability. Glob Environ Change 16:268–281

    Article  Google Scholar 

  • Albuquerque JP, Herfort B, Brenning A, Zipf A (2015) A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. Int J Geogr Inf Sci. doi:10.1080/13658816.2014.996567

    Google Scholar 

  • Anderson MB, Woodrow PJ (1998) Rising from the ashes: development strategies in times of disaster. Lynne Rienner, Boulder

    Google Scholar 

  • Aubrecht C, Meier P, Taubenböck H (2015) Speeding up the clock in remote sensing: identifying the ‘black spots’ in exposure dynamics by capitalizing on the full spectrum of joint high spatial and temporal resolution. Nat Hazards. doi:10.1007/s11069-015-1857-9

  • BBK (2013) Abschätzung der Verwundbarkeit von Bevölkerung und Kritischen Infrastrukturen gegenüber Hitzewellen und Starkregen. Bonn

  • Birkmann J (2013) Measuring vulnerability to promote disaster-resilient societies: conceptual frameworks and definitions. In: Measuring vulnerability to natural hazards: towards disaster resilient societies, 2nd edn. United Nations University Press, Tokyo, pp 9–54

  • Birkmann J, Krings S, Renaud F (2008) Assessment of vulnerability to floods at local level with a special focus on human-environmental systems and critical infrastructures. In: Simonovic SP, Bourget PG, Blanchard SF (eds) Proceedings of the Proceedings of the 4th International Symposium on Flood Defence 6–8 May 2008 Managing Flood Risk, Reliability and Vulnerability; 2008: Institute for Catastrophic Loss Reduction, Toronto

  • Bruneau M, Chang SE, Eguchi RT, Lee GC, O’Rourke TD, Reinhorn AM, Shinozuka M, Tierney K, Wallace WA, von Winterfeld D (2003) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra 19:733–752

    Article  Google Scholar 

  • Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84:242–261

    Article  Google Scholar 

  • Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, Webb J (2008) A place-based model for understanding community resilience. Glob Environ Change 18:598–606

    Article  Google Scholar 

  • Davidson RA, Shah HC (1997) An urban earthquake disaster risk index, stanford digital repository. In: Blume JA (ed) Earthquake Engineering Center Technical Report 121. http://purl.stanford.edu/zy159jm6182

  • de Moel H, Jongman B, Kreibich H, Merz B, Penning-Rowsell E, Ward PJ (2015) Flood risk assessments at different spatial scales. Mitig Adapt Strateg Glob Change 20:865–890

    Article  Google Scholar 

  • de Sherbinin A (2014) Mapping the unmeasurable? Spatial analysis of vulnerability to climate change and climate variability. University of Twente, Enschede

    Google Scholar 

  • Depietri Y, Welle T, Renaud FG (2013) Social vulnerability assessment of the Cologne urban area (Germany) to heat waves: links to ecosystem services. Int J Disaster Risk Reduct 12(6):98–117

    Article  Google Scholar 

  • Engel H (1997) The flood events of 1993/1994 and 1995 in the Rhine River basin. In: Leavesley GH (ed) Destructive water: water-caused natural disasters, their abatement and control, vol 239. IAHS, Wallingford

    Google Scholar 

  • European Commission (2008) COUNCIL DIRECTIVE 2008/114/EC of 8 December 2008 on the Identification and Designation of European Critical Infrastructures and the Assessment of the Need to Improve their Protection, Official Journal of the European Union. 23.12.2008. L 345/75-82. In

  • Fekete A (2011) Common criteria for the assessment of critical infrastructures. Int J Disaster Risk Sci 2:15–24

    Article  Google Scholar 

  • Fekete A (2012) Spatial disaster vulnerability and risk assessments: challenges in their quality and acceptance. Nat Hazards 61:1161–1178

    Article  Google Scholar 

  • Fekete A, Lauwe P, Geier W (2012) Risk management goals and identification of critical infrastructures. Int J Crit Infrastruct 8:336–353

    Article  Google Scholar 

  • Fekete A, Hufschmidt G, Kruse S (2014) Benefits and challenges of resilience and vulnerability for disaster risk management. Int J Disaster Risk Sci 5:3–20

    Article  Google Scholar 

  • Fekete A, Tzavella K, Armas I, Binner J, Garschagen M, Giupponi C, Mojtahed V, Pettita M, Schneiderbauer S, Serre D (2015) Critical data source; tool or even infrastructure? Challenges of geographic information systems and remote sensing for disaster risk governance. ISPRS Int J Geo Inf 4(4):1848–1869. doi:10.3390/ijgi4041848

    Article  Google Scholar 

  • FMIG - Federal Ministry of the Interior of Germany (2009) National Strategy for Critical Infrastructure Protection (CIP Strategy). Berlin

  • Fohringer J, Dransch D, Kreibich H, Schröter K (2015) Social media as an information source for rapid flood inundation mapping. Nat Hazards Earth Syst Sci 15:2725–2738

    Article  Google Scholar 

  • Fraser S, Wood N, Johnston D, Leonard G, Greening P, Rossetto T (2014) Variable population exposure and distributed travel speeds in least-cost Tsunami evacuation modelling. Nat Hazards Earth Syst Sci 14:2975–2991. doi:10.5194/nhess-14-2975-2014

    Article  Google Scholar 

  • GFOCD (2010) Estimation of vulnerability of municipalities towards floods (Abschätzung der Verwundbarkeit gegenüber Hochwasserereignissen auf kommunaler Ebene). Federal Office for Civil Protection and Disaster Assistance, Bonn

    Google Scholar 

  • Glover F, Laguna M (1997) Tabu search. Kluwer Academic Publishers. http://dl.acm.org/citation.cfm?id=549765

  • Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. Geojournal 1–12

  • Goodchild MF, Glennon JA (2010) Crowdsourcing geographic information for disaster response: a research frontier. Int J Digital Earth 3(3):231–241

    Article  Google Scholar 

  • Grünthal G, Thieken AH, Schwarz J, Radtke KS, Smolka A, Merz B (2006) Comparative risk assessments for the city of Cologne: storms, floods, earthquakes. Nat Hazards 38:21–44

    Article  Google Scholar 

  • Herfort B, de Albuquerque JP, Schelhorn S-J, Zipf A (2014) Exploring the geographical relations between social media and flood phenomena to improve situational awareness. In: Connecting a digital Europe through location and place. Springer International Publishing, Cham, pp 55–71

  • Holland JH (1975) Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor. 2nd edn. (1992). MIT Press, Boston

  • Horita FEA, Degrossi LC, Gomes de Assis LF, Zipf A, de Albuquerque JP (2013) The use of volunteered geographic information (VGI) and crowdsourcing in disaster management: a systematic literature review. In: Proceedings of the 19th Americas Conference on Information Systems (AMCIS), p 1

  • Hu Y, Janowicz K (2016) Prioritizing road network connectivity information for disaster response. Retrieved 2 March 2016, http://geog.ucsb.edu/~jano/paper9_EMGIS

  • IKSR (2001) Rheinatlas. Koblenz

  • ISO-International Organization for Standardization (2009) ISO/IEC 31010:2009. Risk management—risk assessment techniques. In: Geneva

  • Jenelius E, Petersen T, Mattsson L-G (2006) Importance and exposure in road network vulnerability analysis. Transp Res Part A Policy Pract 8(40):537–560

    Article  Google Scholar 

  • Karadimas NV, Doukas N, Kolokathi M, Defteraiou G (2008) Routing optimization heuristics algorithms for urban solid waste transportation management. WSEAS Trans Comput 7(12):2022–2031

    Google Scholar 

  • Keller S, Atzl A (2014) Mapping natural hazard impacts on road infrastructure: the extreme precipitation in Baden-Württemberg, Germany, June 2013. Int J Disaster Risk Sci 5:227–241

    Article  Google Scholar 

  • Kern J, Zisgen J (2014) “I like Hochwasser”. Eine stichprobenhafte Untersuchung der Nutzung von Facebook während des Hochwassers 2013 in Deutschland. BBK Bevölkerungsschutz 3:17–19

    Google Scholar 

  • Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680. http://www.jstor.org/stable/1690046. Accessed 22 Mar 2016

  • Kuenzer C, Klein I, Ullmann T, Georgiou EF, Baumhauer R, Dech S (2015) Remote sensing of river delta inundation: exploiting the potential of coarse spatial resolution, temporally-dense MODIS time series. Remote Sens 7:8516–8542

    Article  Google Scholar 

  • Kussul N, Shelestov A, Skakun S (2011) Flood monitoring from SAR data. In: Use of satellite and in-situ data to improve sustainability, Springer, Dordrecht, pp 19–29

  • MEA (2003) Ecosystems and human well-being. A framework for assessment

  • Middleton SE, Middleton L, Modafferi S (2014) Real-time crisis mapping of natural disasters using social media. IEEE Intell Syst 29(2):9–17

    Article  Google Scholar 

  • Moteff J (2005) Risk management and critical infrastructure protection: assessing, integrating, and managing threats, vulnerabilities and consequences. Washington DC

  • Munich RE (2015) Natural catastrophes 2014 Analyses, assessments, positions 2015 issue. Munich

  • Ohder C, Sticher B (2013) Approaches towards a community-oriented and enabling disaster management model. In: Crisis management—Emergency planning—Civil Protection Festschrift on the occasion of 60 years training in civil protection offered by partners, friends and employees of the Federal Office of Civil Protection and Disaster Assistance. Berlin: Duncker & Humblot

  • Ohder C, Röpcke J, Sticher B, Geißler S, Schweer B (2014) Relief Needs and Willingness to Help in the Event of Long-term Power Blackout. Results of a citizen survey in three Berlin districts

  • Pala O, Wilson D, Bent R, Linger S, Arnold J (2014) Accuracy of Service Area Estimation Methods Used for Critical Infrastructure Recovery. In: Critical Infrastructure Protection VIII: 8th IFIP WG 1110 International Conference, ICCIP 2014, Arlington, VA, USA, March 17–19, 2014, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg. pp 173–191

  • Parker M (2001) Planning land information technology research project: efficient recycling collection routing in Pictou County. http://www.cogs.ns.ca/planning/projects/plt20014/images/research.pdf. Accessed 22 Feb 2016

  • Rajabifard A, Coleman D (2012) Towards spatial enablement and beyond. In: Rajabifard A, Coleman D (eds) Spatially enabling government, industry and citizens: research and development perspectives. GSDI Association Press, Needham, pp 9–22

    Google Scholar 

  • Resch B (2013) People as sensors and collective sensing-contextual observations complementing geo- sensor network measurements. In: Krisp JM (ed) Progress in location-based services. Springer, pp 391–406. doi:10.1007/978-3-642-34203-5_22

    Google Scholar 

  • Rhine Atlas 2015 Koblenz; [cited 10.March 2016]. http://www.iksr.org

  • Rinaldi SM, Peerenboom JP, Kelly TK (2001) Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21:11–25

    Article  Google Scholar 

  • Rufat S, Tate E, Burton CG, Maroof AS (2015) Social vulnerability to floods: review of case studies and implications for measurement. Int J Disaster Risk Reduct 4:470–486

    Article  Google Scholar 

  • Stevens D (2007) Geospatial information, sustainable development and decision making in developing countries. In: Geoinformation for development. Herbert Wichmann Verlag, Heidelberg

  • Taubenböck H, Esch T (2011) Remote Sensing: An Effective Data Source for Urban Monitoring. 01.06.2014

  • Taubenböck H, Strunz G (2013) Special issue: remote sensing contributing to mapping earthquake vulnerability and effects. Nat Hazards 68(1)

  • Taubenböck H, Geiß C (2014) Vulnerability and resilience research: a critical perspective. Int J Disaster Risk Sci 5:86–87

    Article  Google Scholar 

  • Turner BL, Kasperson RE, Matson PA, McCarthy JJ, Corell RW, Christensen L, Eckley N, Kasperson JX, Luers A, Martello ML et al (2003) A framework for vulnerability analysis in sustainability science. Proc Natl Acad Sci USA 100:1–6

    Article  Google Scholar 

  • UNISDR (2012) Making Cities Resilient Report 2012. My city is getting ready ! A global snapshot of how local governments reduce disaster risk. Geneva

  • United Nations (2015) Sendai Framework for Disaster Risk Reduction 2015–2030. Geneva

  • US DHS (2013) NIPP 2013: Partnering for Critical Infrastructure Security and Resilience. Washington DC

  • US Government (1996) The President’s Commission on Critical Infrastructure Protection (PCCIP), executive order 13010. Washington DC

  • Ward PJ, Jongman B, Salamon P, Simpson A, Bates P, De Groeve T, Muis S, de Perez EC, Rudari R, Trigg MA et al (2015) Usefulness and limitations of global flood risk models. Nat Clim Change 5:712–715

    Article  Google Scholar 

  • Welle T, Birkmann J (2015) The world risk index: an approach to assess risk and vulnerability on a global scale. J Extreme Events 02:1550003

    Article  Google Scholar 

  • Winn MT (2014) A road network shortest path analysis: applying time-varying travel-time costs for emergency response vehicle routing, Davis County, Utah. http://www.nwmissouri.edu/library/theses/2014/WinnMichael.pdf. Accessed 7 Mar 2016

  • Wurm M, Taubenböck H, Krings S, Birkmann J, Roth A, Dech S Derivation of population distribution for vulnerability assessment in flood-prone German cities using multisensoral remote sensing data 2009. Int Soc Opt Photon

  • Wurm M, Taubenbock H, Roth A, Dech S (2009) Urban structuring using multisensoral remote sensing data: By the example of the German cities Cologne and Dresden 2009: IEEE

Download references

Acknowledgements

We would like to thank the experts for their readiness for the interviews and provision of information. We would like to thank Jessica Bussing and Lukas Edbauer for assistance in certain data search and compilation. We are grateful to the guest editors for inviting us to this paper and thus inspiring us for the work conducted.

Author information

Authors and Affiliations

  1. Institute of Rescue Engineering and Civil Protection, TH Köln - University of Applied Sciences, Betzdorferstr. 2, 50679, Cologne, Germany

    Alexander Fekete & Katerina Tzavella

  2. Lehrstuhl für Geographie Physische Geographie, Institut für Geographie und Geologie, Am Hubland, 97074, Würzburg, Germany

    Roland Baumhauer

Authors
  1. Alexander Fekete
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katerina Tzavella
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Roland Baumhauer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexander Fekete.

Additional information

Special Issue in Natural Hazards: ‘Remote sensing for multiscale mapping of elements at risk’ by Hannes Taubenböck and Christian Geiß.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fekete, A., Tzavella, K. & Baumhauer, R. Spatial exposure aspects contributing to vulnerability and resilience assessments of urban critical infrastructure in a flood and blackout context. Nat Hazards 86 (Suppl 1), 151–176 (2017). https://doi.org/10.1007/s11069-016-2720-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-016-2720-3

Keywords

Search

Navigation