Articles | Volume 20, issue 1
https://doi.org/10.5194/nhess-20-323-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-20-323-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jan 2020
Research article |
| 28 Jan 2020
| 28 Jan 2020
Estimating exposure of residential assets to natural hazards in Europe using open data
Section Hydrology, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Heidi Kreibich
Section Hydrology, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Oswaldo Morales-Nápoles
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
Paweł Terefenko
Institute of Marine and Environmental Sciences, University of Szczecin, Adama Mickiewicza 16, 70-383 Szczecin, Poland
Kai Schröter
Section Hydrology, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
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Cited
22 citations as recorded by crossref.
- A global analysis of extreme coastal water levels with implications for potential coastal overtopping R. Almar et al. 10.1038/s41467-021-24008-9
- Process‐Based Flood Risk Assessment for Germany N. Sairam et al. 10.1029/2021EF002259
- A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran S. Pouyan et al. 10.1038/s41598-021-94266-6
- Residential building stock modelling for mainland China targeted for seismic risk assessment D. Xin et al. 10.5194/nhess-21-3031-2021
- Ensuring the resilience of multi-unit residential buildings (MURBs): a building information modeling (BIM)-based evaluation approach T. Dodanwala & R. Ruparathna 10.1080/23789689.2024.2325261
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- A comprehensive review of Bayesian statistics in natural hazards engineering Y. Zheng et al. 10.1007/s11069-021-04729-2
- A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis R. Harris et al. 10.1016/j.crm.2022.100410
- Toward an adequate level of detail in flood risk assessments T. Sieg et al. 10.1111/jfr3.12889
- BANSHEE–A MATLAB toolbox for Non-Parametric Bayesian Networks D. Paprotny et al. 10.1016/j.softx.2020.100588
- Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data H. Chen et al. 10.1016/j.scitotenv.2021.151289
- Global maps of 3D built-up patterns for urban morphological analysis M. Li et al. 10.1016/j.jag.2022.103048
- Population, land use and economic exposure estimates for Europe at 100 m resolution from 1870 to 2020 D. Paprotny & M. Mengel 10.1038/s41597-023-02282-0
- Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe D. Paprotny et al. 10.1016/j.scitotenv.2020.140011
- Quality of crowdsourced geospatial building information: A global assessment of OpenStreetMap attributes F. Biljecki et al. 10.1016/j.buildenv.2023.110295
- Continental-scale mapping and analysis of 3D building structure M. Li et al. 10.1016/j.rse.2020.111859
- On the role of floodplain storage and hydrodynamic interactions in flood risk estimation M. Farrag et al. 10.1080/02626667.2022.2030058
- Assessing the impact of climate change on fluvial flood losses in urban areas: a case study of Pamplona (Spain) E. Soriano et al. 10.1080/02626667.2023.2246452
- Residential building flood damage: Insights on processes and implications for risk assessments R. Paulik et al. 10.1111/jfr3.12832
- Improving flood impact estimations T. Sieg & A. Thieken 10.1088/1748-9326/ac6d6c
- Modelling national residential building exposure to flooding hazards R. Paulik et al. 10.1016/j.ijdrr.2023.103826
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
22 citations as recorded by crossref.
- A global analysis of extreme coastal water levels with implications for potential coastal overtopping R. Almar et al. 10.1038/s41467-021-24008-9
- Process‐Based Flood Risk Assessment for Germany N. Sairam et al. 10.1029/2021EF002259
- A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran S. Pouyan et al. 10.1038/s41598-021-94266-6
- Residential building stock modelling for mainland China targeted for seismic risk assessment D. Xin et al. 10.5194/nhess-21-3031-2021
- Ensuring the resilience of multi-unit residential buildings (MURBs): a building information modeling (BIM)-based evaluation approach T. Dodanwala & R. Ruparathna 10.1080/23789689.2024.2325261
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- A comprehensive review of Bayesian statistics in natural hazards engineering Y. Zheng et al. 10.1007/s11069-021-04729-2
- A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis R. Harris et al. 10.1016/j.crm.2022.100410
- Toward an adequate level of detail in flood risk assessments T. Sieg et al. 10.1111/jfr3.12889
- BANSHEE–A MATLAB toolbox for Non-Parametric Bayesian Networks D. Paprotny et al. 10.1016/j.softx.2020.100588
- Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data H. Chen et al. 10.1016/j.scitotenv.2021.151289
- Global maps of 3D built-up patterns for urban morphological analysis M. Li et al. 10.1016/j.jag.2022.103048
- Population, land use and economic exposure estimates for Europe at 100 m resolution from 1870 to 2020 D. Paprotny & M. Mengel 10.1038/s41597-023-02282-0
- Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe D. Paprotny et al. 10.1016/j.scitotenv.2020.140011
- Quality of crowdsourced geospatial building information: A global assessment of OpenStreetMap attributes F. Biljecki et al. 10.1016/j.buildenv.2023.110295
- Continental-scale mapping and analysis of 3D building structure M. Li et al. 10.1016/j.rse.2020.111859
- On the role of floodplain storage and hydrodynamic interactions in flood risk estimation M. Farrag et al. 10.1080/02626667.2022.2030058
- Assessing the impact of climate change on fluvial flood losses in urban areas: a case study of Pamplona (Spain) E. Soriano et al. 10.1080/02626667.2023.2246452
- Residential building flood damage: Insights on processes and implications for risk assessments R. Paulik et al. 10.1111/jfr3.12832
- Improving flood impact estimations T. Sieg & A. Thieken 10.1088/1748-9326/ac6d6c
- Modelling national residential building exposure to flooding hazards R. Paulik et al. 10.1016/j.ijdrr.2023.103826
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
Latest update: 18 Apr 2024
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 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 square metre of floor space for 30 countries.
Houses and their contents in Europe are worth trillions of euros, resulting in high losses from...
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