Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.883 IF 2.883
  • IF 5-year value: 3.321 IF 5-year
    3.321
  • CiteScore value: 3.07 CiteScore
    3.07
  • SNIP value: 1.336 SNIP 1.336
  • IPP value: 2.80 IPP 2.80
  • SJR value: 1.024 SJR 1.024
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 81 Scimago H
    index 81
  • h5-index value: 43 h5-index 43
Discussion papers
https://doi.org/10.5194/nhess-2019-313
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-313
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 30 Sep 2019

Submitted as: research article | 30 Sep 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Estimating exposure of residential assets to natural hazards in Europe using open data

Dominik Paprotny1, Heidi Kreibich1, Oswaldo Morales-Nápoles2, Paweł Terefenko3, and Kai Schröter1 Dominik Paprotny et al.
  • 1Section Hydrology, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
  • 2Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, The Netherlands
  • 3Institute of Marine and Environmental Sciences, University of Szczecin, Adama Mickiewicza 18, 70-383 Szczecin, Poland

Abstract. Natural hazards affect many types of tangible assets, the most valuable of which are often residential assets, comprising buildings and household contents. Yet, information necessary to derive exposure in terms of monetary value at the level of individual houses is often not available. This includes building type, size, quality or age. In this study, we provide a universal method for estimating exposure of residential assets using only publicly-available or open data. Using building footprints (polygons) from OpenStreetMap as a starting point, we utilized high-resolution elevation models of 30 European capitals and a set of pan-European raster dataset to construct a Bayesian Network-based model that is able to predict building height. The model was then validated with a dataset of: (1) buildings in Poland endangered by sea level rise, for which the number of floors is known, and (2) a sample of Dutch and German houses affected in the past by fluvial and pluvial floods, for which usable floor space area is known. Floor space of buildings is an important basis for approximating their economic value, including household contents. Here, we provide average national-level gross replacement costs of the stock of residential assets in 30 European countries, in nominal and real prices, covering years 2000–2017. We relied either on existing estimates of the total stock of assets or made new calculations using the Perpetual Inventory Method, which were then translated into exposure per m2 of floor space using data on countries' dwelling stocks. The study shows that the resulting standardized residential exposure values provide much better coverage and consistency compared to previous studies.

Dominik Paprotny et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Dominik Paprotny et al.
Dominik Paprotny et al.
Viewed  
Total article views: 363 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
267 93 3 363 21 4 4
  • HTML: 267
  • PDF: 93
  • XML: 3
  • Total: 363
  • Supplement: 21
  • BibTeX: 4
  • EndNote: 4
Views and downloads (calculated since 30 Sep 2019)
Cumulative views and downloads (calculated since 30 Sep 2019)
Viewed (geographical distribution)  
Total article views: 228 (including HTML, PDF, and XML) Thereof 224 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 07 Dec 2019
Publications Copernicus
Download
Short summary
Houses and their contents in Europe are worth trillions of euros, resulting in high losses from natural hazards. Hence, risk assessments need to reliably estimate the size and value of houses, including the value of durable goods that are kept inside. In this work we show how openly available or open datasets can be used to predict the size of individual residential buildings. Further, we provide standardized monetary values of houses and contents per m2 of floor space for 30 countries.
Houses and their contents in Europe are worth trillions of euros, resulting in high losses from...
Citation