Articles | Volume 16, issue 2
https://doi.org/10.5194/nhess-16-417-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-16-417-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Feb 2016
Research article |
| 10 Feb 2016
Using open building data in the development of exposure data sets for catastrophe risk modelling
R. Figueiredo
CORRESPONDING AUTHOR
Institute for Advanced Study of Pavia, Pavia, Italy
European Centre for Training and Research in Earthquake Engineering, Pavia, Italy
M. Martina
Institute for Advanced Study of Pavia, Pavia, Italy
European Centre for Training and Research in Earthquake Engineering, Pavia, Italy
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Cited
28 citations as recorded by crossref.
- A Probabilistic Paradigm for the Parametric Insurance of Natural Hazards R. Figueiredo et al. 10.1111/risa.13122
- 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
- Assessing 40 Years of Flood Risk Evolution at the Micro-Scale Using an Innovative Modeling Approach: The Effects of Urbanization and Land Planning T. Lazzarin et al. 10.3390/geosciences13040112
- Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru J. Gomez-Zapata et al. 10.5194/nhess-21-3599-2021
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- Seamless Estimation of Hydrometeorological Risk Across Spatial Scales T. Sieg et al. 10.1029/2018EF001122
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
- Assessment of Urban Thermal Environments Using a Combination of the Local Climate Zone and Landscape Ecological Metrics in Taipei City Y. Chen et al. 10.1061/JUPDDM.UPENG-4890
- A methodology for flood susceptibility and vulnerability analysis in complex flood scenarios F. Dottori et al. 10.1111/jfr3.12234
- Residential building stock modelling for mainland China targeted for seismic risk assessment D. Xin et al. 10.5194/nhess-21-3031-2021
- Flood exposure analysis of road infrastructure – Comparison of different methods at national level T. Papilloud et al. 10.1016/j.ijdrr.2020.101548
- Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts E. Duo et al. 10.1016/j.envint.2020.105884
- Generating 3D city models without elevation data F. Biljecki et al. 10.1016/j.compenvurbsys.2017.01.001
- Identifying spatial clusters of flood exposure to support decision making in risk management V. Röthlisberger et al. 10.1016/j.scitotenv.2017.03.216
- Flood risk assessment of cultural heritage at large spatial scales: Framework and application to mainland Portugal R. Figueiredo et al. 10.1016/j.culher.2019.11.007
- Calculating earthquake damage building by building: the case of the city of Cologne, Germany C. Nievas et al. 10.1007/s10518-021-01303-w
- Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China J. Wu et al. 10.3390/su11040971
- Crowdsourcing Exposure Data for Seismic Vulnerability Assessment in Developing Countries I. Grigoratos et al. 10.1080/13632469.2018.1537901
- Vulnerability Assessment with Scarce Information for a Quantitative Flood Risk Model. Case Study Monteria-Colombia H. Hoyos & B. Botero 10.1088/1757-899X/471/10/102005
- Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
- Better understanding of climate catastrophe insurance in China: issues and opportunities, international insights, and directions for development F. Kong & Y. Wang 10.1007/s11069-022-05501-w
- Towards a Sensitivity Analysis in Seismic Risk with Probabilistic Building Exposure Models: An Application in Valparaíso, Chile Using Ancillary Open-Source Data and Parametric Ground Motions J. Gómez Zapata et al. 10.3390/ijgi11020113
- Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy A. Taramelli et al. 10.5194/nhess-22-3543-2022
- Better Understanding the Catastrophe Risk in Interconnection and Comprehensive Disaster Risk Defense Capability, with Special Reference to China F. Kong & S. Sun 10.3390/su13041793
- Integrating asset-specific flood vulnerability assessments with value-based preservation processes to develop the Heritage Building Flood Robustness Toolkit R. Snelling et al. 10.1016/j.culher.2023.11.025
- Accuracy of FEMA-Hazus Single-Family Residential Damage Exposure Data in Houston: Implications for Using or Correcting the Hazus General Building Stock S. Shultz 10.1061/(ASCE)NH.1527-6996.0000484
- Loss assessment of building and contents damage from the potential earthquake risk in Seoul, South Korea W. Choi et al. 10.5194/nhess-19-985-2019
- Component-based flood vulnerability modelling for cultural heritage buildings R. Figueiredo et al. 10.1016/j.ijdrr.2021.102323
28 citations as recorded by crossref.
- A Probabilistic Paradigm for the Parametric Insurance of Natural Hazards R. Figueiredo et al. 10.1111/risa.13122
- 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
- Assessing 40 Years of Flood Risk Evolution at the Micro-Scale Using an Innovative Modeling Approach: The Effects of Urbanization and Land Planning T. Lazzarin et al. 10.3390/geosciences13040112
- Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru J. Gomez-Zapata et al. 10.5194/nhess-21-3599-2021
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- Seamless Estimation of Hydrometeorological Risk Across Spatial Scales T. Sieg et al. 10.1029/2018EF001122
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
- Assessment of Urban Thermal Environments Using a Combination of the Local Climate Zone and Landscape Ecological Metrics in Taipei City Y. Chen et al. 10.1061/JUPDDM.UPENG-4890
- A methodology for flood susceptibility and vulnerability analysis in complex flood scenarios F. Dottori et al. 10.1111/jfr3.12234
- Residential building stock modelling for mainland China targeted for seismic risk assessment D. Xin et al. 10.5194/nhess-21-3031-2021
- Flood exposure analysis of road infrastructure – Comparison of different methods at national level T. Papilloud et al. 10.1016/j.ijdrr.2020.101548
- Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts E. Duo et al. 10.1016/j.envint.2020.105884
- Generating 3D city models without elevation data F. Biljecki et al. 10.1016/j.compenvurbsys.2017.01.001
- Identifying spatial clusters of flood exposure to support decision making in risk management V. Röthlisberger et al. 10.1016/j.scitotenv.2017.03.216
- Flood risk assessment of cultural heritage at large spatial scales: Framework and application to mainland Portugal R. Figueiredo et al. 10.1016/j.culher.2019.11.007
- Calculating earthquake damage building by building: the case of the city of Cologne, Germany C. Nievas et al. 10.1007/s10518-021-01303-w
- Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China J. Wu et al. 10.3390/su11040971
- Crowdsourcing Exposure Data for Seismic Vulnerability Assessment in Developing Countries I. Grigoratos et al. 10.1080/13632469.2018.1537901
- Vulnerability Assessment with Scarce Information for a Quantitative Flood Risk Model. Case Study Monteria-Colombia H. Hoyos & B. Botero 10.1088/1757-899X/471/10/102005
- Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
- Better understanding of climate catastrophe insurance in China: issues and opportunities, international insights, and directions for development F. Kong & Y. Wang 10.1007/s11069-022-05501-w
- Towards a Sensitivity Analysis in Seismic Risk with Probabilistic Building Exposure Models: An Application in Valparaíso, Chile Using Ancillary Open-Source Data and Parametric Ground Motions J. Gómez Zapata et al. 10.3390/ijgi11020113
- Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy A. Taramelli et al. 10.5194/nhess-22-3543-2022
- Better Understanding the Catastrophe Risk in Interconnection and Comprehensive Disaster Risk Defense Capability, with Special Reference to China F. Kong & S. Sun 10.3390/su13041793
- Integrating asset-specific flood vulnerability assessments with value-based preservation processes to develop the Heritage Building Flood Robustness Toolkit R. Snelling et al. 10.1016/j.culher.2023.11.025
- Accuracy of FEMA-Hazus Single-Family Residential Damage Exposure Data in Houston: Implications for Using or Correcting the Hazus General Building Stock S. Shultz 10.1061/(ASCE)NH.1527-6996.0000484
- Loss assessment of building and contents damage from the potential earthquake risk in Seoul, South Korea W. Choi et al. 10.5194/nhess-19-985-2019
- Component-based flood vulnerability modelling for cultural heritage buildings R. Figueiredo et al. 10.1016/j.ijdrr.2021.102323
Saved (preprint)
Latest update: 23 Apr 2024
Short summary
The building exposure component of risk models is frequently based on census data at coarse resolutions. Spatial disaggregation into finer resolutions is usually performed based on proxy variables, which is a reasonable but not ideal procedure. The availability of open data is increasing and these data can be taken into account in order to generate more accurate exposure models, which in turn can improve the results of risk models. A method to do so is proposed and its limitations are analysed.
The building exposure component of risk models is frequently based on census data at coarse...
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