Multi-level geospatial modeling of human exposure

Christoph Aubrecht, Dilek Özceylan Aubrecht, Klaus Steinnocher, Sergio Freie

Research output: Contribution to journalArticlepeer-review

Abstract

In the context of disaster risk management and in particular for improving preparedness and mitigation of potential impacts, information on socioeconomic characteristics including aspects of situation-specific human exposure and vulnerability is considered vital. This paper provides an overview on available multi-level geospatial information and modeling approaches from global to local scales that could serve as inventory for people involved in disaster-related areas. Concepts and applications related to the human exposure and social vulnerability domains are addressed by illustrating the varying dimensions and contextual implications. Datasets and methods are highlighted that can be applied to assess earthquake-related population exposure, ranging from global and continental-scale population grids (with a focus on recent developments for Europe) to high-resolution functional urban system models and space-time variation aspects. In a further step, the paper elaborates on the integration of social structure on regional scale and the development of aggregative social and economic vulnerability indicators which would eventually enable the differentiation of situation-specific risk patterns. The presented studies cover social vulnerability mapping for selected US federal states in the New Madrid seismic zone as well as the advancement of social vulnerability analysis through integration of additional economic features in the index construction by means of a case study for Turkey´s provinces.
Original languageEnglish
Pages (from-to)147-163
Number of pages17
JournalNatural Hazards
Publication statusPublished - 2013

Research Field

  • Outside the AIT Research Fields

Keywords

  • Multi-level geospatial information Spatial disaggregation Population grid

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