LitPop: Global Exposure Data for Disaster Risk Assessment
Asset exposure data for global physical risk assessment
dc.contributor.author
Eberenz, Samuel
dc.contributor.author
Stocker, Dario
dc.contributor.author
Röösli, Thomas
dc.contributor.author
Bresch, David N.
dc.contributor.contactPerson
Eberenz, Samuel
dc.contributor.researchGroup
Bresch, David N.
dc.date.accessioned
2020-04-30T15:28:00Z
dc.date.available
2019-03-14T09:51:15Z
dc.date.available
2019-03-18T08:45:33Z
dc.date.available
2019-03-28T12:46:02Z
dc.date.available
2020-04-09T14:29:37Z
dc.date.available
2020-04-14T15:53:01Z
dc.date.available
2020-04-28T20:05:57Z
dc.date.available
2020-04-29T09:50:45Z
dc.date.available
2020-04-29T10:30:42Z
dc.date.available
2020-04-30T15:28:00Z
dc.date.created
2019-03
en_US
dc.date.issued
2019-03
dc.identifier.uri
http://hdl.handle.net/20.500.11850/331316
dc.identifier.doi
10.3929/ethz-b-000331316
dc.description.abstract
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 make gridded asset exposure data for 224 countries at a resolution of 30 arcsec available for download.
For more information, please refer to the accompanying publication. Please cite this publication, if you are using the data:
Eberenz, S., Stocker, D., Röösli, T., and Bresch, D. N.: Asset exposure data for global physical risk assessment, Earth Syst. Sci. Data, 12, 817–833, https://doi.org/10.5194/essd-12-817-2020, 2020.
en_US
dc.format
text/plain
en_US
dc.format
text/csv
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dc.format
application/x-tar
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Asset exposure data
en_US
dc.subject
Exposed assets
en_US
dc.subject
Global
en_US
dc.subject
Night lights
en_US
dc.subject
Population data
en_US
dc.subject
Produced capital
en_US
dc.subject
Downscaling
en_US
dc.subject
Downscaling approach
en_US
dc.title
LitPop: Global Exposure Data for Disaster Risk Assessment
en_US
dc.type
Dataset
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2019-03-18
ethz.title.subtitle
Asset exposure data for global physical risk assessment
en_US
ethz.size
16.63 GB
en_US
ethz.version.edition
v1.2 (2020-04-09)
en_US
ethz.code.ddc
DDC - DDC::3 - Social sciences::300 - Social sciences
en_US
ethz.geolocation.placename
global
ethz.publication.place
Zurich
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02723 - Institut für Umweltentscheidungen / Institute for Environmental Decisions::09576 - Bresch, David Niklaus / Bresch, David Niklaus
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02723 - Institut für Umweltentscheidungen / Institute for Environmental Decisions::09576 - Bresch, David Niklaus / Bresch, David Niklaus
en_US
ethz.date.retentionend
indefinite
en_US
ethz.date.retentionendDate
n/a
ethz.relation.isCitedBy
10.3929/ethz-b-000398592
ethz.relation.isCitedBy
10.3929/ethz-b-000489485
ethz.relation.isDocumentedBy
10.3929/ethz-b-000409595
ethz.date.deposited
2019-03-14T09:51:24Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.identifier.internal
LitPop
en_US
ethz.availability
Open access
en_US
ethz.description.methods
Gridded physical asset values per country. National total physical asset values downscaled proportionally to the normalised product of nightlight intensity (Lit, based on NASA Earth at Night [1]) and population count (Pop, based on Gridded Population of the World, Version 4.1 [2]).
Gridded exposure is computed with the LitPop-module of the probabilistic natural catastrophe damage model CLIMADA [3]. Please refer to the accompanying publication [4] and the tutorial [5] for more information.
National total physical asset values are produced capital of 2014 from The World Bank's "Wealth Accounting" [6] (available for 140 countries). Alternatively, non-financial wealth is estimated from the country's GDP in 2014 and the GDP-to-wealth ratios as estimated in the Credit Suisse Research Institute's "Global Wealth Report 2017" [7] (used for 84 countries).
Gridded normalised Lit and Pop are provided for 14 selected country as used in the validation of the LitPop exposure data model [2].
The Python 3.6 script to reproduce this data is available at https://github.com/CLIMADA-project/climada_papers.
References:
[1] NASA Earth Observatory, 2017. Earth at Night: Flat Maps. Avaible at: earthobservatory.nasa.gov/features/NightLights/page3.php. (last access: January 2020)
[2] Socioeconomic Data and Applications Center (SEDAC): Country-level Information and Sources Revision 10, avail- able at: https://beta.sedac.ciesin.columbia.edu/data/set/ gpw-v4-admin-unit-center-points-population-estimates-rev10/docs, 2017. (last access: 4 April 2020)
[3] Python version of CLIMADA. https://github.com/CLIMADA-project/climada_python/ (last accessed April 2020)
[4] Publication: https://doi.org/10.5194/essd-12-817-2020 (last accessed April 2020)
[5] Tutorial: https://climada-python.readthedocs.io/en/latest/tutorial/climada_entity_LitPop.html (last accessed April 2020)
[6] The World Bank. "Wealth Accounting": https://datacatalog.worldbank.org/dataset/wealth-accounting (last accessed April 2020)
[7] Credit Suisse Research Institute. "Global Wealth Report 2017", 2017. https://www.credit-suisse.com/corporate/en/articles/news-and-expertise/global-wealth-report-2017-201711.html (last accessed March 2019)
en_US
ethz.description.software
CLIMADA – global weather and climate risk assessment platform.
Open-source software (Python 3.6+), available on GitHub:
https://github.com/CLIMADA-project/climada_python
https://github.com/CLIMADA-project/climada_papers
en_US
ethz.rosetta.installDate
2019-03-18T16:37:38Z
ethz.rosetta.lastUpdated
2022-03-29T02:01:33Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=LitPop:%20Global%20Exposure%20Data%20for%20Disaster%20Risk%20Assessment&rft.date=2019-03&rft.au=Eberenz,%20Samuel&Stocker,%20Dario&R%C3%B6%C3%B6sli,%20Thomas&Bresch,%20David%20N.&rft.genre=unknown&rft.btitle=LitPop:%20Global%20Exposure%20Data%20for%20Disaster%20Risk%20Assessment
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