toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
  Record Links
Author (up) Eberenz, S.; Stocker, D.; Röösli, T.; Bresch, D.N. url  doi
  Title Asset exposure data for global physical risk assessment Type Journal Article
  Year 2020 Publication Earth System Science Data Abbreviated Journal Earth Syst. Sci. Data  
  Volume 12 Issue 2 Pages 817-833  
  Keywords Economics  
  Abstract One of the challenges in globally consistent assessments of physical climate risks is the fact thatasset exposure data are either unavailable or restricted to single countries or regions. We introduce a globalhigh-resolution asset exposure dataset responding to this challenge. The data are produced using “lit population”(LitPop), a globally consistent methodology to disaggregate asset value data proportional to a combination ofnightlight intensity and geographical population data. By combining nightlight and population data, unwantedartefacts such as blooming, saturation, and lack of detail are mitigated. Thus, the combination of both data typesimproves the spatial distribution of macroeconomic indicators. Due to the lack of reported subnational assetdata, the disaggregation methodology cannot be validated for asset values. Therefore, we compare disaggregatedgross domestic product (GDP) per subnational administrative region to reported gross regional product (GRP)values for evaluation. The comparison for 14 industrialized and newly industrialized countries shows that thedisaggregation skill for GDP using nightlights or population data alone is not as high as using a combinationof both data types. The advantages of LitPop are global consistency, scalability, openness, replicability, and lowentry threshold. The open-source LitPop methodology and the publicly available asset exposure data offer valuefor manifold use cases, including globally consistent economic disaster risk assessments and climate changeadaptation studies, especially for larger regions, yet at considerably high resolution. The code is published onGitHub as part of the open-source software CLIMADA (CLIMate ADAptation) and archived in the ETH DataArchive with the link (Bresch et al., 2019b). The resulting asset exposuredataset for 224 countries is archived in the ETH Research Repository with the link (Eberenz et al., 2019).  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1866-3516 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2883  
Permanent link to this record
Select All    Deselect All
 |   | 

Save Citations:
Export Records: