Abstract
For assessing the social dimension of vulnerability, population exposure mapping is usually considered the essential starting point. Integration of social structure then further differentiates situation-specific vulnerability patterns on a local scale. Census data available in heterogeneous spatial reference units are still considered the standard information input for assessing potentially affected people, for example, in case of an emergency. There is a strong demand for population data in homogeneous spatial units that are independent from administrative areas. Raster representations meet this demand but are not yet available for all European countries. In this paper, we present an approach of spatial disaggregation of population data for a European transect referring to current population statistics and anticipated future prospects. Recently published data providing the degree of soil sealing are applied as basic proxy for population density in the spatial disaggregation model. In order to assess future patterns of climate change-related vulnerability, results of a European regional climate model are considered for projecting the situation in the 2030s. “Heat wave frequency” is accounted for as climate variable featuring conditions regarded as especially strenuous for elderly or physically weak persons. Integrated analysis of the population and climate prospects enables identification of hot spots in the European transect examined, that is, regions of particularly demanding projected climatic patterns as well as high population density and case-specific vulnerable structure (elderly people). Integrated and consistent spatial analyses on European scale are essential for decision support in the context of climate change impact mitigation as well as for risk communication and future safety and security considerations.
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Notes
Considered an extension and further elaboration of the explanations in Aubrecht et al. (2011b).
NUTS Nomenclature of Units for Territorial Statistics, a geocode standard of the European Union for referencing the subdivisions of countries for statistical purposes; a hierarchy of three NUTS levels is established for all EU member countries by Eurostat.
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Acknowledgments
Part of the study was performed within the Core Information Service for Spatial Planning of the project geoland2 (http://www.gmes-geoland.info/) in the frame of the GMES (Global Monitoring for Environment and Security) initiative. The project geoland2 is a Collaborative Project (2008–2012) funded by the European Union under the 7th Framework Programme (project number FP-7-218795).
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Aubrecht, C., Steinnocher, K., Köstl, M. et al. Long-term spatio-temporal social vulnerability variation considering health-related climate change parameters particularly affecting elderly. Nat Hazards 68, 1371–1384 (2013). https://doi.org/10.1007/s11069-012-0324-0
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DOI: https://doi.org/10.1007/s11069-012-0324-0