Articles | Volume 21, issue 10
https://doi.org/10.5194/nhess-21-3199-2021
https://doi.org/10.5194/nhess-21-3199-2021
Research article
 | 
27 Oct 2021
Research article |  | 27 Oct 2021

Improving flood damage assessments in data-scarce areas by retrieval of building characteristics through UAV image segmentation and machine learning – a case study of the 2019 floods in southern Malawi

Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel

Related authors

Reflections and Future Directions for Multi-Hazard Risk in the Context of the Sendai Framework and Discussions Beyond
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771,https://doi.org/10.5194/egusphere-2025-2771, 2025
This preprint is open for discussion and under review for Geoscience Communication (GC).
Short summary
Bridging Science and Practice on Multi-Hazard Risk Drivers: Stakeholder Insights from Five Pilot Studies in Europe
Nicole van Maanen, Marleen de Ruiter, Wiebke Jäger, Veronica Casartelli, Roxana Ciurean, Noemi Padron, Anne Sophie Daloz, David Geurts, Stefania Gottardo, Stefan Hochrainer-Stigler, Abel López Diez, Jaime Díaz Pacheco, Pedro Dorta Antequera, Tamara Febles Arévalo, Sara García González, Raúl Hernández-Martín, Carmen Alvarez-Albelo, Juan José Diaz-Hernandez, Lin Ma, Letizia Monteleone, Karina Reiter, Tristian Stolte, Robert Šakić Trogrlić, Silvia Torresan, Sharon Tatman, David Romero Manrique de Lara, Yeray Hernández González, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-3075,https://doi.org/10.5194/egusphere-2025-3075, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Covariance-informed spatiotemporal clustering improves the detection of hazardous weather events
Hunter C. Quintal, Antonia Sebastian, Marc L. Serre, Wiebke S. Jäger, and Marleen C. de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2025-2870,https://doi.org/10.5194/egusphere-2025-2870, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Assessing future impacts of tropical cyclones on global banana production
Sophie Kaashoek, Žiga Malek, Nadia Bloemendaal, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 25, 1963–1974, https://doi.org/10.5194/nhess-25-1963-2025,https://doi.org/10.5194/nhess-25-1963-2025, 2025
Short summary
Increasing flood risk in the Indian Ganga Basin: A perspective from the night-time lights
Ekta Aggarwal, Marleen C. de Ruiter, Kartikeya S. Sangwan, Rajiv Sinha, Sophie Buijs, Ranjay Shrestha, Sanjeev Gupta, and Alexander C. Whittaker
EGUsphere, https://doi.org/10.5194/egusphere-2024-3901,https://doi.org/10.5194/egusphere-2024-3901, 2025
Preprint archived
Short summary

Related subject area

Hydrological Hazards
Drought propagation in high-latitude catchments: insights from a 60-year analysis using standardized indices
Claudia Teutschbein, Thomas Grabs, Markus Giese, Andrijana Todorović, and Roland Barthel
Nat. Hazards Earth Syst. Sci., 25, 2541–2564, https://doi.org/10.5194/nhess-25-2541-2025,https://doi.org/10.5194/nhess-25-2541-2025, 2025
Short summary
Brief communication: Hydrological and hydraulic investigation of the extreme September 2024 flood on the Lamone River in Emilia-Romagna, Italy
Alessia Ferrari, Giulia Passadore, Renato Vacondio, Luca Carniello, Mattia Pivato, Elena Crestani, Francesco Carraro, Francesca Aureli, Sara Carta, Francesca Stumpo, and Paolo Mignosa
Nat. Hazards Earth Syst. Sci., 25, 2473–2479, https://doi.org/10.5194/nhess-25-2473-2025,https://doi.org/10.5194/nhess-25-2473-2025, 2025
Short summary
Improving pluvial flood simulations with a multi-source digital elevation model super-resolution method
Yue Zhu, Paolo Burlando, Puay Yok Tan, Christian Geiß, and Simone Fatichi
Nat. Hazards Earth Syst. Sci., 25, 2271–2286, https://doi.org/10.5194/nhess-25-2271-2025,https://doi.org/10.5194/nhess-25-2271-2025, 2025
Short summary
It could have been much worse: spatial counterfactuals of the July 2021 flood in the Ahr Valley, Germany
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 25, 2007–2029, https://doi.org/10.5194/nhess-25-2007-2025,https://doi.org/10.5194/nhess-25-2007-2025, 2025
Short summary
Rapid high-resolution impact-based flood early warning is possible with RIM2D: a showcase for the 2023 pluvial flood in Braunschweig
Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schröter, and Max Steinhausen
Nat. Hazards Earth Syst. Sci., 25, 1737–1749, https://doi.org/10.5194/nhess-25-1737-2025,https://doi.org/10.5194/nhess-25-1737-2025, 2025
Short summary

Cited articles

Ai, J., Zhang, C., Chen, L., and Li, D.: Mapping Annual Land Use and Land Cover Changes in the Yangtze Estuary Region Using an Object-Based Classification Framework and Landsat Time Series Data, Sustainability, 12, 659, https://doi.org/10.3390/su12020659, 2020. 
Alam, A., Bhat, M. S., Farooq, H., Ahmad, B., Ahmad, S., and Sheikh, A. H.: Flood risk assessment of Srinagar city in Jammu and Kashmir, India, International Journal of Disaster Resilience in the Built Environment, 9, 114–129, https://doi.org/10.1108/IJDRBE-02-2017-0012, 2018. 
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. 
Belgiu, M. and Draguţ, L.: Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery, ISPRS J. Photogramm., 96, 67–75, https://doi.org/10.1016/j.isprsjprs.2014.07.002, 2014. 
Blanco-Vogt, Á., Haala, N., and Schanze, J.: Building parameters extraction from remote-sensing data and GIS analysis for the derivation of a building taxonomy of settlements – a contribution to flood building susceptibility assessment, International Journal of Image and Data Fusion, 6, 22–41, https://doi.org/10.1080/19479832.2014.926296, 2015. 
Download
Short summary
This research introduces a novel approach to estimate flood damage in Malawi by applying a machine learning model to UAV imagery. We think that the development of such a model is an essential step to enable the swift allocation of resources for recovery by humanitarian decision-makers. By comparing this method (EUR 10 140) to a conventional land-use-based approach (EUR 15 782) for a specific flood event, recommendations are made for future assessments.
Share
Altmetrics
Final-revised paper
Preprint