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ESSD | Articles | Volume 12, issue 2
Earth Syst. Sci. Data, 12, 817–833, 2020
https://doi.org/10.5194/essd-12-817-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 12, 817–833, 2020
https://doi.org/10.5194/essd-12-817-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Data description paper 09 Apr 2020

Data description paper | 09 Apr 2020

Asset exposure data for global physical risk assessment

Samuel Eberenz et al.

Data sets

LitPop: Global Exposure Data for Disaster Risk Assessment S. Eberenz, D. Stocker, T. Röösli, and D. N. Bresch https://doi.org/10.3929/ethz-b-000331316

Model code and software

CLIMADA v.1.2.0 D. N. Bresch, G. Aznar Siguan, S. Eberenz, T. Röösli, D. Stocker, J. Hartman, M. Pérus, and V. Bozzini https://doi.org/10.5905/ethz-1007-226

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Short summary
The modeling of economic disaster risk on a global scale requires high-resolution maps of exposed asset values. We have developed a generic and scalable method to downscale national asset value estimates proportional to a combination of nightlight intensity and population data. Here, we present the methodology together with an evaluation of its performance for the subnational downscaling of GDP. The resulting exposure data for 224 countries and the open-source Python code are available online.
The modeling of economic disaster risk on a global scale requires high-resolution maps of...
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