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dc.contributor.authorTENERELLI PATRIZIAen_GB
dc.contributor.authorGALLEGO PINILLA FRANCISCOen_GB
dc.contributor.authorEHRLICH DANIELEen_GB
dc.date.accessioned2017-07-09T00:20:37Z-
dc.date.available2017-07-07en_GB
dc.date.available2017-07-09T00:20:37Z-
dc.date.created2017-07-03en_GB
dc.date.issued2015en_GB
dc.date.submitted2014-09-15en_GB
dc.identifier.citationINTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION vol. 13 p. 334-341en_GB
dc.identifier.issn2212-4209en_GB
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S2212420915300431?via%3Dihuben_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC91725-
dc.description.abstractDemographic data is a fundamental component of an earthquake loss model for the estimation of human exposure and social vulnerability. Fine scale population distribution information is needed for the assessment of causalities, determination of shelter needs and proper implementation of evacuation plans in pre- and/or post-disaster phases, i.e. earthquake scenario modelling and rapid emergency response. This paper describes the techniques that are used to map the population distribution, and to integrate the building damage information with demographic data for casualty estimation. Methods to map population density are described focusing on different downscaling techniques and the contribution of ancillary data. An application for the Larger Urban Zone (LUZ) of Vienna is illustrated. The case study disaggregates the residential population from a local and a country level census at the level of single building blocks. The downscaling is based on a dasymetric approach using an urban land use map as ancillary information. The model was applied after testing two different methods: a limiting variable and a fixed-ratio method. The latter performed slightly better and was applied on the entire study area. The results of the proposed methodology can be used to perform population vulnerability analysis for night time scenarios which deals mainly with residential building typologies. The enhanced spatial detail influences the accuracy of the information on human exposure when the population map is used in risk assessment models.en_GB
dc.description.sponsorshipJRC.E.1-Disaster Risk Managementen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE BVen_GB
dc.relation.ispartofseriesJRC91725en_GB
dc.titlePopulation density modelling in support of seismic risk assessmenten_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1016/j.ijdrr.2015.07.015en_GB
JRC Directorate:Space, Security and Migration

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