Articles | Volume 21, issue 2
https://doi.org/10.5194/nhess-21-643-2021
https://doi.org/10.5194/nhess-21-643-2021
Research article
 | 
16 Feb 2021
Research article |  | 16 Feb 2021

Are OpenStreetMap building data useful for flood vulnerability modelling?

Marco Cerri, Max Steinhausen, Heidi Kreibich, and Kai Schröter

Related authors

Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood
Belinda Rhein and Heidi Kreibich
EGUsphere, https://doi.org/10.5194/egusphere-2024-2066,https://doi.org/10.5194/egusphere-2024-2066, 2024
Short summary
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024,https://doi.org/10.5194/nhess-24-2025-2024, 2024
Short summary
Adaptive Behavior of Over a Million Individual Farmers Under Consecutive Droughts: A Large-Scale Agent-Based Modeling Analysis in the Bhima Basin, India
Maurice W. M. L. Kalthof, Jens de Bruijn, Hans de Moel, Heidi Kreibich, and Jeroen C. J. H. Aerts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1588,https://doi.org/10.5194/egusphere-2024-1588, 2024
Short summary
Flood damage model bias caused by aggregation
Seth Bryant, Heidi Kreibich, and Bruno Merz
Proc. IAHS, 386, 181–187, https://doi.org/10.5194/piahs-386-181-2024,https://doi.org/10.5194/piahs-386-181-2024, 2024
Short summary
Invited perspectives: Safeguarding the usability and credibility of flood hazard and risk assessments
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
EGUsphere, https://doi.org/10.5194/egusphere-2024-856,https://doi.org/10.5194/egusphere-2024-856, 2024
Short summary

Related subject area

Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Micro-business participation in collective flood adaptation: lessons from scenario-based analysis in Ho Chi Minh City, Vietnam
Javier Revilla Diez, Roxana Leitold, Van Tran, and Matthias Garschagen
Nat. Hazards Earth Syst. Sci., 24, 2425–2440, https://doi.org/10.5194/nhess-24-2425-2024,https://doi.org/10.5194/nhess-24-2425-2024, 2024
Short summary
Brief communication: Storm Daniel flood impact in Greece in 2023: mapping crop and livestock exposure from synthetic-aperture radar (SAR)
Kang He, Qing Yang, Xinyi Shen, Elias Dimitriou, Angeliki Mentzafou, Christina Papadaki, Maria Stoumboudi, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 24, 2375–2382, https://doi.org/10.5194/nhess-24-2375-2024,https://doi.org/10.5194/nhess-24-2375-2024, 2024
Short summary
Risk reduction through managed retreat? Investigating enabling conditions and assessing resettlement effects on community resilience in Metro Manila
Hannes Lauer, Carmeli Marie C. Chaves, Evelyn Lorenzo, Sonia Islam, and Jörn Birkmann
Nat. Hazards Earth Syst. Sci., 24, 2243–2261, https://doi.org/10.5194/nhess-24-2243-2024,https://doi.org/10.5194/nhess-24-2243-2024, 2024
Short summary
Brief communication: Lessons learned and experiences gained from building up a global survey on societal resilience to changing droughts
Marina Batalini de Macedo, Marcos Roberto Benso, Karina Simone Sass, Eduardo Mario Mendiondo, Greicelene Jesus da Silva, Pedro Gustavo Câmara da Silva, Elisabeth Shrimpton, Tanaya Sarmah, Da Huo, Michael Jacobson, Abdullah Konak, Nazmiye Balta-Ozkan, and Adelaide Cassia Nardocci
Nat. Hazards Earth Syst. Sci., 24, 2165–2173, https://doi.org/10.5194/nhess-24-2165-2024,https://doi.org/10.5194/nhess-24-2165-2024, 2024
Short summary
Regional seismic risk assessment based on ground conditions in Uzbekistan
Vakhitkhan Alikhanovich Ismailov, Sharofiddin Ismatullayevich Yodgorov, Akhror Sabriddinovich Khusomiddinov, Eldor Makhmadiyorovich Yadigarov, Bekzod Uktamovich Aktamov, and Shuhrat Bakhtiyorovich Avazov
Nat. Hazards Earth Syst. Sci., 24, 2133–2146, https://doi.org/10.5194/nhess-24-2133-2024,https://doi.org/10.5194/nhess-24-2133-2024, 2024
Short summary

Cited articles

Alfieri, L., Feyen, L., Salamon, P., Thielen, J., Bianchi, A., Dottori, F., and Burek, P.: Modelling the socio-economic impact of river floods in Europe, Nat. Hazards Earth Syst. Sci., 16, 1401–1411, https://doi.org/10.5194/nhess-16-1401-2016, 2016. a
Amadio, M., Scorzini, A. R., Carisi, F., Essenfelder, A. H., Domeneghetti, A., Mysiak, J., and Castellarin, A.: Testing empirical and synthetic flood damage models: the case of Italy, Nat. Hazards Earth Syst. Sci., 19, 661–678, https://doi.org/10.5194/nhess-19-661-2019, 2019. a
Amirebrahimi, S., Rajabifard, A., Mendis, P., and Ngo, T.: A framework for a microscale flood damage assessment and visualization for a building using BIM–GIS integration, Int. J. Digit. Earth, 9, 363–386, https://doi.org/10.1080/17538947.2015.1034201, 2016. a
Apel, H., Aronica, G. T., Kreibich, H., and Thieken, A.: Flood risk analyses–how detailed do we need to be?, Nat. Hazards, 49, 79–98, https://doi.org/10.1007/s11069-008-9277-8, 2009. a, b
Barrington-Leigh, C. and Millard-Ball, A.: The world’s user-generated road map is more than 80 % complete, Plos One, 12, 1–20, https://doi.org/10.1371/journal.pone.0180698, 2017. a, b
Download
Short summary
Effective flood management requires information about the potential consequences of flooding. We show how openly accessible data from OpenStreetMap can support the estimation of flood damage for residential buildings. Working with methods of machine learning, the building geometry is used to predict flood damage in combination with information about inundation depth. Our approach makes it easier to transfer models to regions where no detailed data of flood impacts have been observed yet.
Altmetrics
Final-revised paper
Preprint