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| Titel |
Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) – a case study for Bucharest, Romania |
| VerfasserIn |
I. Armas, A. Gavriș |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 13, no. 6 ; Nr. 13, no. 6 (2013-06-18), S.1481-1499 |
| Datensatznummer |
250018496
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| Publikation (Nr.) |
 copernicus.org/nhess-13-1481-2013.pdf |
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| Zusammenfassung |
| In recent decades, the development of vulnerability frameworks has enlarged the
research in the natural hazards field. Despite progress in developing the
vulnerability studies, there is more to investigate regarding the
quantitative approach and clarification of the conceptual explanation of the social
component. At the same time, some disaster-prone areas register limited
attention. Among these, Romania's capital city, Bucharest, is the most
earthquake-prone capital in Europe and the tenth in the world. The location
is used to assess two multi-criteria methods for aggregating complex
indicators: the social vulnerability index (SoVI model) and the spatial
multi-criteria social vulnerability index (SEVI model). Using the data of the
2002 census we reduce the indicators through a factor analytical approach to
create the indices and examine if they bear any resemblance to the known
vulnerability of Bucharest city through an exploratory spatial data analysis
(ESDA). This is a critical issue that may provide better understanding of the
social vulnerability in the city and appropriate information for authorities
and stakeholders to consider in their decision making. The study emphasizes
that social vulnerability is an urban process that increased in a
post-communist Bucharest, raising the concern that the population at risk
lacks the capacity to cope with disasters. The assessment of the indices
indicates a significant and similar clustering pattern of the census
administrative units, with an overlap between the clustering areas affected
by high social vulnerability. Our proposed SEVI model suggests adjustment
sensitivity, useful in the expert-opinion accuracy. |
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