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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.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Samuel Eberenz on behalf of the Authors (11 Feb 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (20 Feb 2020) by David Carlson
RR by Anonymous Referee #2 (09 Mar 2020)
ED: Publish subject to technical corrections (09 Mar 2020) by David Carlson
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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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