Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

IF value: 9.197
IF9.197
IF 5-year value: 9.612
IF 5-year
9.612
CiteScore value: 12.5
CiteScore
12.5
SNIP value: 3.137
SNIP3.137
IPP value: 9.49
IPP9.49
SJR value: 4.532
SJR4.532
Scimago H <br class='widget-line-break'>index value: 48
Scimago H
index
48
h5-index value: 35
h5-index35
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.

Viewed

Total article views: 1,730 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,318 376 36 1,730 69 37 32
  • HTML: 1,318
  • PDF: 376
  • XML: 36
  • Total: 1,730
  • Supplement: 69
  • BibTeX: 37
  • EndNote: 32
Views and downloads (calculated since 29 Oct 2019)
Cumulative views and downloads (calculated since 29 Oct 2019)

Viewed (geographical distribution)

Total article views: 1,444 (including HTML, PDF, and XML) Thereof 1,405 with geography defined and 39 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

No saved metrics found.

Saved (preprint)

No saved metrics found.

Discussed (final revised paper)

No discussed metrics found.

Discussed (preprint)

No discussed metrics found.
Latest update: 23 Nov 2020
Download
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...
Citation