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A global exposure model for disaster risk assessment

dc.creatorA. De Bono
dc.creatorM. G. Mora
dc.date.accessioned2016-07-28T13:28:58Z
dc.date.available2016-07-28T13:28:58Z
dc.date.issued2014
dc.identifier.citationA. De Bono, M. G. Mora. (2014). A global exposure model for disaster risk assessment . Ginebra. International Journal of Disaster Risk Reduction
dc.identifier.urihttp://hdl.handle.net/20.500.11762/19781
dc.identifier.urihttps://doi.org/10.1016/j.ijdrr.2014.05.008
dc.description.sponsorshipCentro Internacional de Métodos Numéricos e Ingeniería - CIMNE, Universidad de Ginebra, United Nations Environment Programme - UNEP
dc.formatDigital (.pdf)
dc.language.isoen
dc.publisherInternational Journal of Disaster Risk Reduction
dc.source© Elsevier
dc.sourceinstname:Unidad Nacional para la Gestión del Riesgo de Desastresspa
dc.sourcereponame:Repositorio Institucional Unidad Nacional para la Gestión del Riesgo de Desastresspa
dc.subjectUrbano
dc.subjectelementos expuestos
dc.subjectpoblación
dc.subjectGAR
dc.subjectDownscale
dc.subjectCapital urbano
dc.titleA global exposure model for disaster risk assessment
dc.typeinfo:eu-repo/semantics/articlespa
dc.description.departamentoGINEBRA
dc.type.spaArticulo de investigación
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessspa
dc.description.abstractenglish"The global exposure database is being produced for the global risk assessment 2013, part of the Global Assessment Report (GAR 2013). It aims to map at a granular geographical level the world`s capital stock in urban areas. It is designed primarily to assess the risk of economic losses as consequence of natural hazards at a global scale. The Global Exposure database for GAR 2013 is an open exposure global dataset at 5 km spatial resolution which integrates population and country-specific building typology, use and value. It is currently suitable mainly for earthquakes and cyclones probabilistic risk modeling using CAPRA platform. This paper describes the development of the GAR 2013. The database is based on a top-down or ""downscaling"" approach of national/regional socio-economic and building type information. These information are transposed onto a regular raster dataset (grid format) using a geographic population distribution model as a proxy. "
dc.identifier.doiInternational Journal of Disaster Risk Reduction 10(2014)442-451
dc.identifier.doihttps://doi.org/10.1016/j.ijdrr.2014.05.008
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S2212420914000478
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionspa


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