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Titel
Spatial vulnerability units : expert-based spatial modelling of socio-economic vulnerability in the Salzach catchment, Austria
VerfasserKienberger, Stefan ; Lang, S. ; Zeil, P.
Erschienen in
Natural Hazards and Earth System Science, Basel, 2009, Jg. 2009, H. 9, S. 767-778
ErschienenMDPI, 2009
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
URNurn:nbn:at:at-ubs:3-6074 Persistent Identifier (URN)
DOI10.5194/nhess-9-767-2009 
Zugriffsbeschränkung
 Das Werk ist frei verfügbar
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Spatial vulnerability units [33.38 mb]
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Zusammenfassung (Englisch)

The assessment of vulnerability has moved to centre-stage of the debate between different scientific disciplines related to climate change and disaster risk management. Composed by a combination of social, economical, physical and environmental factors the assessment implies combining different domains as well as quantitative with qualitative data and makes it therefore a challenge to identify an integrated metric for vulnerability. In this paper we define vulnerability in the context of climate change, targeting the hazard "flood". The developed methodology is being tested in the Salzach river catchment in Austria, which is largely prone to floods. The proposed methodology allows the spatial quantification of vulnerability and the identification of vulnerability units. These units build upon the geon concept which acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information. Considering the fact that vulnerability is not directly measurable and due to its complex dimension and social construction an expert-based approach has been chosen. Established methodologies such as Multicriteria Decision Analysis, Delphi exercises and regionalization approaches are being integrated. The method not only enables the assessment of vulnerability independent from administrative boundaries, but also applies an aggregation mode which reflects homogenous vulnerability units. This supports decision makers to reflect on complex issues such as vulnerability. Next to that, the advantage is to decompose the units to their underlying domains. Feedback from disaster management experts indicates that the approach helps to improve the design of measures aimed at strengthening preparedness and mitigation. From this point of view, we reach a step closer towards validation of the proposed method, comprising critical user-oriented aspects like adequateness, practicability and usability of the provided results in general.