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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-213
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-213
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Jul 2020

10 Jul 2020

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A revised version of this preprint is currently under review for the journal NHESS.

A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest

Sebastian Scheuer1, Dagmar Haase1,3, Annegret Haase2, Manuel Wolff1, and Thilo Wellmann1,3 Sebastian Scheuer et al.
  • 1Landscape Ecology Lab, Geography Department, Humboldt-Universität zu Berlin, Berlin, 10099, Germany
  • 2Department of Urban and Environmental Sociology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, 04318, Germany
  • 3Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318 Leipzig, Germany

Abstract. Disaster risk is conceived as the interaction of hazard, exposure, and vulnerability. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the residence of urban dwellers. This case study for the city of Leipzig, Germany, proposes an indirect, machine learning-based approach for the prediction of residential choice behaviour to explore how exposure and vulnerabilities are shaped by the residential location choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.

Sebastian Scheuer et al.

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Sebastian Scheuer et al.

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Short summary
The choice of residential location is one of the drivers shaping risks in cities. We model likely outcomes of this decision-making process for distinct socioeconomic groups in the city of Leipzig, Germany, using random forests and geostatistical methods. In so doing, we uncover hot spots and cold spots that may indicate spatial patterns and trends in exposure and vulnerabilities of urban population, to shed a light on how residential location choice affects these risk components as a process.
The choice of residential location is one of the drivers shaping risks in cities. We model...
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