Articles | Volume 21, issue 10
https://doi.org/10.5194/nhess-21-3199-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-3199-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Oct 2021
Research article |
| 27 Oct 2021
| 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
CORRESPONDING AUTHOR
Institute for Environmental studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, the Netherlands
510, an initiative of the Netherlands Red Cross, Anna van Saksenlaan 50, 2593 HT Den Haag, the Netherlands
Anaïs Couasnon
Institute for Environmental studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, the Netherlands
Marleen C. de Ruiter
Institute for Environmental studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, the Netherlands
Marc J. C. van den Homberg
510, an initiative of the Netherlands Red Cross, Anna van Saksenlaan 50, 2593 HT Den Haag, the Netherlands
Aklilu Teklesadik
510, an initiative of the Netherlands Red Cross, Anna van Saksenlaan 50, 2593 HT Den Haag, the Netherlands
Hans de Moel
Institute for Environmental studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, the Netherlands
Related authors
No articles found.
Sophie L. Buijs, Inga J. Sauer, Chahan M. Kropf, Samuel Juhel, Zélie Stalhandske, and Marleen C. De Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2025-3200, https://doi.org/10.5194/egusphere-2025-3200, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
We studied how repeated disasters affect recovery across housing, health, economic systems, and governance. Our findings show that failing to recover fully between events can increase long-term risks but also offers opportunities for learning and adaptation. Understanding these dynamics can help societies plan better, reduce vulnerability, and build resilience to increasingly frequent and severe hazards.
Wiebke S. Jäger, Marleen C. de Ruiter, Timothy Tiggeloven, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 25, 2751–2769, https://doi.org/10.5194/nhess-25-2751-2025, https://doi.org/10.5194/nhess-25-2751-2025, 2025
Short summary
Short summary
Multiple hazards, occurring simultaneously or consecutively, can have more extreme impacts than single hazards. We examined the disaster records in the global emergency events database EM-DAT to better understand this phenomenon. We developed a method to identify such multi-hazards and analysed their reported impacts using statistics. Multi-hazards have accounted for a disproportionate number of the impacts, but there appear to be different archetypal patterns in which the impacts compound.
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
Short summary
Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
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
Short summary
Disaster risk management faces growing challenges from multiple, changing hazards. Interviews with stakeholders in five European regions reveal that climate change, urban growth, and socio-economic shifts increase vulnerability and exposure. Measures to reduce one risk can worsen others, highlighting the need for better coordination. The study calls for flexible, context-specific strategies that connect scientific risk assessments with real-world decision-making.
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
Short summary
High quality weather event datasets are crucial to community preparedness and resilience. Researchers create such datasets using clustering methods, which we advance by addressing current limitation in the relationship between space and time. We propose a method to determine the appropriate factor by which to resample the spatial resolution of the data prior to clustering. Ultimately, our approach increases the ability to detect historic heatwaves over current methods.
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
Short summary
Tropical storms are expected to get stronger all over the world, and this will have a big impact on people, buildings and important activities like growing bananas. Already, in different parts of the world, banana farms are being hurt by these storms, which makes banana prices go up and affects the people who grow them. We are not sure how these storms will affect bananas everywhere in the future. We assessed what happened to banana farms during storms in different parts of the world.
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
Short summary
The occurrence of frequent floods in recent years due to changing weather, heavy rainfall, and the natural landscape, has caused major damage to lives and property. This study looks at flood risks in the Ganga Basin, focusing on the factors that cause floods, the areas affected, and the vulnerability of people. The study uses NASA's night-time lights to track human activities. This helps to show how risks are connected to expanding human activities, and changing resilience to floods.
Maurice W. M. L. Kalthof, Jens de Bruijn, Hans de Moel, Heidi Kreibich, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 25, 1013–1035, https://doi.org/10.5194/nhess-25-1013-2025, https://doi.org/10.5194/nhess-25-1013-2025, 2025
Short summary
Short summary
Our study explores how farmers in India's Bhima basin respond to consecutive droughts. We simulated farmers' individual choices – like changing crops or digging wells – and their effects on profits, yields, and water resources. Results show these adaptations, while improving incomes, ultimately increase drought vulnerability and damage. Such insights emphasize the need for alternative adaptations and highlight the value of socio-hydrological models in shaping policies to lessen drought impacts.
Julius Schlumberger, Tristian Stolte, Helena Margaret Garcia, Antonia Sebastian, Wiebke Jäger, Philip Ward, Marleen de Ruiter, Robert Šakić Trogrlić, Annegien Tijssen, and Mariana Madruga de Brito
EGUsphere, https://doi.org/10.5194/egusphere-2025-850, https://doi.org/10.5194/egusphere-2025-850, 2025
Short summary
Short summary
The risk flood of flood impacts is dynamic as society continuously responds to specific events or ongoing developments. We analyzed 28 studies that assess such dynamics of vulnerability. Most research uses surveys and basic statistics data, while integrated, flexible models are seldom used. The studies struggle to link specific events or developments to the observed changes. Our findings highlight needs and possible directions towards a better assessment of vulnerability dynamics.
Nivedita Sairam and Marleen de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2025-920, https://doi.org/10.5194/egusphere-2025-920, 2025
Short summary
Short summary
This paper highlights gaps in disaster risk assessments, particularly regarding disease outbreaks after natural hazards. It calls for: 1) learning from compound risk models to understand disaster and disease probabilities, 2) including health metrics in risk frameworks, and 3) improving data and modeling for health impacts. The authors propose a research agenda to enhance disaster risk management.
Joshua Green, Ivan D. Haigh, Niall Quinn, Jeff Neal, Thomas Wahl, Melissa Wood, Dirk Eilander, Marleen de Ruiter, Philip Ward, and Paula Camus
Nat. Hazards Earth Syst. Sci., 25, 747–816, https://doi.org/10.5194/nhess-25-747-2025, https://doi.org/10.5194/nhess-25-747-2025, 2025
Short summary
Short summary
Compound flooding, involving the combination or successive occurrence of two or more flood drivers, can amplify flood impacts in coastal/estuarine regions. This paper reviews the practices, trends, methodologies, applications, and findings of coastal compound flooding literature at regional to global scales. We explore the types of compound flood events, their mechanistic processes, and the range of terminology. Lastly, this review highlights knowledge gaps and implications for future practices.
Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, W. J. Wouter Botzen, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 24, 4409–4429, https://doi.org/10.5194/nhess-24-4409-2024, https://doi.org/10.5194/nhess-24-4409-2024, 2024
Short summary
Short summary
As sea levels rise, coastal areas will experience more frequent flooding, and salt water will start seeping into the soil, which is a serious issue for farmers who rely on good soil quality for their crops. Here, we studied coastal Mozambique to understand the risks from sea level rise and flooding by looking at how salt intrusion affects farming and how floods damage buildings. We find that 15 %–21 % of coastal households will adapt and 13 %–20 % will migrate to inland areas in the future.
Julius Schlumberger, Robert Šakić Trogrlić, Jeroen C. J. H. Aerts, Jung-Hee Hyun, Stefan Hochrainer-Stigler, Marleen de Ruiter, and Marjolijn Haasnoot
EGUsphere, https://doi.org/10.5194/egusphere-2024-3655, https://doi.org/10.5194/egusphere-2024-3655, 2024
Short summary
Short summary
This study presents a dashboard to help decision-makers manage risks in a changing climate. Using interactive visualizations, it simplifies complex choices, even with uncertain information. Tested with 54 users of varying expertise, it enabled accurate responses to 71–80 % of questions. Users valued its scenario exploration and detailed data features. While effective, the guidance and set of visualizations could be extended and the prototype could be adapted for broader applications.
Gwendoline Ducros, Timothy Tiggeloven, Lin Ma, Anne Sophie Daloz, Nina Schuhen, and Marleen C. de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2024-3158, https://doi.org/10.5194/egusphere-2024-3158, 2024
Short summary
Short summary
Our study finds that heatwave, drought and wildfire events occurring simultaneously in Scandinavia are pronounced in the summer months; and the heat-drought 2018 event led to a drop in gross domestic product, affecting agriculture and forestry imports, further impacting Europe’s trade balance. This research shows the importance of ripple effects of multi-hazard, and that forest management and adaptation measures are vital to reducing the risks of heat-related multi-hazards in vulnerable areas.
Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, and Monica L. Turner
Nat. Hazards Earth Syst. Sci., 24, 309–329, https://doi.org/10.5194/nhess-24-309-2024, https://doi.org/10.5194/nhess-24-309-2024, 2024
Short summary
Short summary
We improve an existing impact forecasting model for the Philippines by transforming the target variable (percentage of damaged houses) to a fine grid, using only features which are globally available. We show that our two-stage model conserves the performance of the original and even has the potential to introduce savings in anticipatory action resources. Such model generalizability is important in increasing the applicability of such tools around the world.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
Short summary
Short summary
There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Rhoda A. Odongo, Hans De Moel, and Anne F. Van Loon
Nat. Hazards Earth Syst. Sci., 23, 2365–2386, https://doi.org/10.5194/nhess-23-2365-2023, https://doi.org/10.5194/nhess-23-2365-2023, 2023
Short summary
Short summary
We characterize meteorological (P), soil moisture (SM) and hydrological (Q) droughts and the propagation from one to the other for 318 catchments in the Horn of Africa. We find that propagation from P to SM is influenced by soil properties and vegetation, while propagation from P to Q is from catchment-scale hydrogeological properties (i.e. geology, slope). We provide precipitation accumulation periods at the subbasin level that can be used as a proxy in drought forecasting in dryland regions.
Job C. M. Dullaart, Sanne Muis, Hans de Moel, Philip J. Ward, Dirk Eilander, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 23, 1847–1862, https://doi.org/10.5194/nhess-23-1847-2023, https://doi.org/10.5194/nhess-23-1847-2023, 2023
Short summary
Short summary
Coastal flooding is driven by storm surges and high tides and can be devastating. To gain an understanding of the threat posed by coastal flooding and to identify areas that are especially at risk, now and in the future, it is crucial to accurately model coastal inundation and assess the coastal flood hazard. Here, we present a global dataset with hydrographs that represent the typical evolution of an extreme sea level. These can be used to model coastal inundation more accurately.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
Short summary
Short summary
In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
Short summary
Short summary
The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Agathe Bucherie, Micha Werner, Marc van den Homberg, and Simon Tembo
Nat. Hazards Earth Syst. Sci., 22, 461–480, https://doi.org/10.5194/nhess-22-461-2022, https://doi.org/10.5194/nhess-22-461-2022, 2022
Short summary
Short summary
Local communities in northern Malawi have well-developed knowledge of the conditions leading to flash floods, spatially and temporally. Scientific analysis of catchment geomorphology and global reanalysis datasets corroborates this local knowledge, underlining the potential of these large-scale scientific datasets. Combining local knowledge with contemporary scientific datasets provides a common understanding of flash flood events, contributing to a more people-centred warning to flash floods.
Marleen Carolijn de Ruiter, Anaïs Couasnon, and Philip James Ward
Geosci. Commun., 4, 383–397, https://doi.org/10.5194/gc-4-383-2021, https://doi.org/10.5194/gc-4-383-2021, 2021
Short summary
Short summary
Many countries can get hit by different hazards, such as earthquakes and floods. Generally, measures and policies are aimed at decreasing the potential damages of one particular hazard type despite their potential of having unwanted effects on other hazard types. We designed a serious game that helps professionals to improve their understanding of these potential negative effects of measures and policies that reduce the impacts of disasters across many different hazard types.
Jens A. de Bruijn, James E. Daniell, Antonios Pomonis, Rashmin Gunasekera, Joshua Macabuag, Marleen C. de Ruiter, Siem Jan Koopman, Nadia Bloemendaal, Hans de Moel, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-282, https://doi.org/10.5194/nhess-2020-282, 2020
Revised manuscript not accepted
Short summary
Short summary
Following hurricanes and other natural hazards, it is important to quickly estimate the damage caused by the hazard such that recovery aid can be granted from organizations such as the European Union and the World Bank. To do so, it is important to estimate the vulnerability of buildings to the hazards. In this research, we use post-disaster observations from social media to improve these vulnerability assessments and show its application in the Bahamas following Hurricane Dorian.
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.
Blaschke, T.: Object based image analysis for remote sensing, ISPRS J. Photogramm., 65, 2–16, https://doi.org/10.1016/j.isprsjprs.2009.06.004, 2010.
Budiyono, Y., Aerts, J., Brinkman, J., Marfai, M. A., and Ward, P.: Flood risk assessment for delta mega-cities: A case study of Jakarta, Nat. Hazards, 75, 389–413, https://doi.org/10.1007/s11069-014-1327-9, 2015.
CAPRA: Probabilistic Risk Assessment Program, ERN-Vulnerability v2, available at: https://ecapra.org/ (last access: 8 May 2019), 2012.
Cian, F., Marconcini, M., Ceccato, P., and Giupponi, C.: Flood depth estimation by means of high-resolution SAR images and lidar data, Nat. Hazards Earth Syst. Sci., 18, 3063–3084, https://doi.org/10.5194/nhess-18-3063-2018, 2018.
CIESIN.: Facebook Connectivity Lab and Center for International Earth Science Information Network. High Resolution Settlement Layer (HRSL), Center for International Earth Science Information Network, available at: https://www.ciesin.columbia.edu/data/hrsl/ (last access: 21 April 2019), 2016.
Cohen, S., Brakenridge, G. R., Kettner, A., Bates, B., Nelson, J., McDonald, R., Huang, Y.-F., Munasinghe, D., and Zhang, J.: Estimating Floodwater Depths from Flood Inundation Maps and Topography, J. Am. Water Resour. As., 54, 847–858. https://doi.org/10.1111/1752-1688.12609, 2018.
Copier, W., de Ruiter, M. C., de Moel, H., Couasnon, A. A., and Teklesadik, A.: The impact of drone data on hydraulic modelling – A case study for an area in Malawi, Vrije Universiteit Amsterdam, Amsterdam, 2019.
De Angeli, S., Dell'Acqua, F., and Trasforini, E.: Application of an Earth-Observation-based building exposure mapping tool for flood damage assessment, E3S Web Conf., 7, 05001, https://doi.org/10.1051/e3sconf/20160705001, 2016.
de Moel, H. and Aerts, J. C. J. H.: Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates, Nat. Hazards, 58, 407–425, https://doi.org/10.1007/s11069-010-9675-6, 2011.
de Moel, H., Asselman, N. E. M., and Aerts, J. C. J. H.: Uncertainty and sensitivity analysis of coastal flood damage estimates in the west of the Netherlands, Nat. Hazards Earth Syst. Sci., 12, 1045–1058, https://doi.org/10.5194/nhess-12-1045-2012, 2012.
de Moel, H., Jongman, B., Kreibich, H., Merz, B., Penning-Rowsell, E., and Ward, P. J.: Flood risk assessments at different spatial scales, Mitig. Adapt. Strat. Gl., 20, 865–890, https://doi.org/10.1007/s11027-015-9654-z, 2015.
de Ruiter, M. C., Ward, P. J., Daniell, J. E., and Aerts, J. C. J. H.: Review Article: A comparison of flood and earthquake vulnerability assessment indicators, Nat. Hazards Earth Syst. Sci., 17, 1231–1251, https://doi.org/10.5194/nhess-17-1231-2017, 2017.
Díaz-Delgado, C. and Gaytán Iniestra, J.: Flood Risk Assessment in Humanitarian Logistics Process Design, J. Appl. Res. Technol., 12, 976–984, https://doi.org/10.1016/S1665-6423(14)70604-2, 2014.
Englhardt, J., de Moel, H., Huyck, C. K., de Ruiter, M. C., Aerts, J. C. J. H., and Ward, P. J.: Enhancement of large-scale flood risk assessments using building-material-based vulnerability curves for an object-based approach in urban and rural areas, Nat. Hazards Earth Syst. Sci., 19, 1703–1722, https://doi.org/10.5194/nhess-19-1703-2019, 2019.
Farr, T. G. and Kobrick, M.: Shuttle radar topography mission produces a wealth of data, Eos, 81, 583, https://doi.org/10.1029/EO081i048p00583, 2000.
Fekete, A.: Spatial disaster vulnerability and risk assessments: Challenges in their quality and acceptance, Nat. Hazards, 61, 1161–1178, https://doi.org/10.1007/s11069-011-9973-7, 2012.
Government of Malawi: 2015 Floods Post Disaster Needs Assessment Report – Malawi, Government of Malawi, available at: https://reliefweb.int/report/malawi/malawi-2015-floods-post-disaster-needs-assessment-report (last access: 26 May 2019), 2015.
Grizonnet, M., Michel, J., Poughon, V., Inglada, J., Savinaud, M., and Cresson, R.: Orfeo ToolBox: Open-source processing of remote sensing images, Open Geospatial Data, Software and Standards, 2, 15, https://doi.org/10.1186/s40965-017-0031-6, 2017.
Gutierrez, I., Før Gjermundsen, E., Harcourt, W. D., Kuschnerus, M., Tonion, F., and Zieher, T.: Analysis of filtering techniques for investigating landslide-induced topographic changes in the oetz valley (Tyrol, Austria), ISPRS Annual Photogrammetry Remote Sensing and Spatial Information Sciences, V-2-2020, 719–726, https://doi.org/10.5194/isprs-annals-V-2-2020-719-2020, 2020.
Hosmer, D. W. and Lemeshow, S.: Applied logistic regression, Second edition, John Wiley and Sons Inc., USA, New York, 2000.
Hydrologic Engineering Center: HEC-RAS, River Analysis System User's Manual, Version 3.1, Davis, California, 1998.
IFRC: Malawi Floods: Emergency Plan of Action (EPoA), International Federation of Red Cross And Red Crescent Societies, available at: https://reliefweb.int/sites/reliefweb.int/files/resources/MDRMW014do.pdf, last access: 5 April 2019.
Jones, B.: Managing Post-Disaster Needs Assessments (PDNA), Managing Post-Disaster Needs Assessments (PDNA), World Bank, Washington, DC., EAP DRM Knowledge Notes, 19, 8, 2010.
Jongman, B., Kreibich, H., Apel, H., Barredo, J. I., Bates, P. D., Feyen, L., Gericke, A., Neal, J., Aerts, J. C. J. H., and Ward, P. J.: Comparative flood damage model assessment: towards a European approach, Nat. Hazards Earth Syst. Sci., 12, 3733–3752, https://doi.org/10.5194/nhess-12-3733-2012, 2012.
Kamps, M., Bouten, W., and Seijmonsbergen, A. C.: LiDAR and Orthophoto Synergy to optimize Object-Based Landscape Change: Analysis of an Active Landslide, Remote Sens., 9, 805, https://doi.org/10.3390/rs9080805, 2017.
Ke, Q., Jonkman, S. N., Van Gelder, P. H. a. J. M., and Rijcken, T.: Flood damage estimation for downtown Shanghai sensitivity analysis. Conference of the International Society for Integrated Disaster Risk Management IDRiM 2012, Authors Version: International Society for Integrated Disaster Risk Management, Beijing, China, available at: https://repository.tudelft.nl/islandora/object/uuid%3Abf75cdab-8a0d-4dbf-ae8e-61f59d3e5d86 (last access: 21 May 2019), 2012.
Klemas, V. V.: Coastal and Environmental Remote Sensing from Unmanned Aerial Vehicles: An Overview, J. Coastal Res., 31, 1260–1267, https://doi.org/10.2112/JCOASTRES-D-15-00005.1, 2015.
Koks, E. E., Bočkarjova, M., de Moel, H., and Aerts, J. C. J. H.: Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis, Computat. Studies, 35, 882–900, https://doi.org/10.1111/risa.12300, 2015.
Maiti, S.: Defining a Flood Risk Assessment Procedure using Community Based Approach with Integration of Remote Sensing and GIS, International Institute for Geo-information Science and Earth Observation, Enschede, 2007.
Malawi Statistical Office: Fourth Integrated Household Survey (IHS4) 2016–2017, Ministry of Economic Planning and Development (MoEPD), Zomba, 2017.
Malgwi, M. B., Fuchs, S., and Keiler, M.: A generic physical vulnerability model for floods: review and concept for data-scarce regions, Nat. Hazards Earth Syst. Sci., 20, 2067–2090, https://doi.org/10.5194/nhess-20-2067-2020, 2020.
Malgwi M. B., Schlögl, M. and Keiler, M.: Expert-based versus data-driven flood damage models: A comparative evaluation for data-scarce regions, Int. J. Disast. Risk Re., 57, 102148, ISSN 2212-4209, https://doi.org/10.1016/j.ijdrr.2021.102148, 2021.
Mallupattu, P. K. and Sreenivasula Reddy, J. R.: Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India, Sci. World J., 2013, e268623, https://doi.org/10.1155/2013/268623, 2013.
McVittie, A.: Sentinel-1 Flood mapping tutorial, Skywatch, ESA, available at: http://step.esa.int/docs/tutorials/tutorial_s1floodmapping.pdf (last access: 26 April 2019), 2019.
Merz, B., Kreibich, H., Thieken, A., and Schmidtke, R.: Estimation uncertainty of direct monetary flood damage to buildings, Nat. Hazards Earth Syst. Sci., 4, 153–163, https://doi.org/10.5194/nhess-4-153-2004, 2004.
Merz, B., Kreibich, H., Schwarze, R., and Thieken, A.: Review article ”Assessment of economic flood damage”, Nat. Hazards Earth Syst. Sci., 10, 1697–1724, https://doi.org/10.5194/nhess-10-1697-2010, 2010.
Michel, J., Youssefi, D., and Grizonnet, M.: Stable Mean-Shift Algorithm and Its Application to the Segmentation of Arbitrarily Large Remote Sensing Images, IEEE T. Geosci. Remote, 53, 952–964, https://doi.org/10.1109/TGRS.2014.2330857, 2015.
Mountrakis, G., Im, J., and Ogole, C.: Support vector machines in remote sensing: A review, ISPRS J. Photogramm., 66, 247–259, https://doi.org/10.1016/j.isprsjprs.2010.11.001, 2011.
Mouratidis, A. and Sarti, F.: Flash-Flood Monitoring and Damage Assessment with SAR Data: Issues and Future Challenges for Earth Observation from Space Sustained by Case Studies from the Balkans and Eastern Europe, in: Earth Observation of Global Changes (EOGC), edited by: Krisp, J. M., Meng, L., Pail, R., and Stilla, U., 125–136, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-32714-8_8, 2013.
Murnane, R. J., Daniell, J. E., Schäfer, A. M., Ward, P. J., Winsemius, H. C., Simpson, A., Tijssen, A., and Toro, J.: Future scenarios for earthquake and flood risk in Eastern Europe and Central Asia, Earth's Future, 5, 693–714, https://doi.org/10.1002/2016EF000481, 2017.
Nowak Da Costa, J., Calka, B., and Bielecka, E.: Urban Population Flood Impact Applied to a Warsaw Scenario, Resources, 10, 62, https://doi.org/10.3390/resources10060062, 2021.
OpenStreetMap contributors.: © OpenStreetMap, available at: https://www.openstreetmap.org, last access: 2 July 2019.
Rudari, R., Beckers, J., De Angeli, S., Rossi, L., and Trasforini, E.: Impact of modelling scale on probabilistic flood risk assessment: the Malawi case, 3rd European Conference on Flood Risk Management (FLOODrisk 2016), Savona, Italy, https://doi.org/10.1051/e3sconf/20160704015, 2016.
Saint-Geours, N., Lavergne, C., Bailly, J.-S., and Grelot, F.: Ranking sources of uncertainty in flood damage modelling: A case study on the cost-benefit analysis of a flood mitigation project in the Orb Delta, France, J. Flood Risk Manag., 8, 161–176, https://doi.org/10.1111/jfr3.12068, 2015.
Shen, X., Wang, D., Mao, K., Anagnostou, E., and Hong, Y.: Inundation Extent Mapping by Synthetic Aperture Radar: A Review., Remote Sens., 11, 879, https://doi.org/10.3390/rs11070879, 2019.
SNAP: European Space Agency Sentinel Application Platform v6.0, ESA, available at: http://step.esa.int, last access: 5 June 2019.
Starkey, E., Parkin, G., Birkinshaw, S., Large, A., Quinn, P., and Gibson, C.: Demonstrating the value of community-based (“citizen science”) observations for catchment modelling and characterisation, J. Hydrol., 548, 801–817, https://doi.org/10.1016/j.jhydrol.2017.03.019, 2017.
Teule, T., Couasnon, A., Bischiniotis, K., Blasch, J., and van den Homberg, M.: Towards improving a national flood early warning system with global ensemble flood predictions and local knowledge; a case study on the Lower Shire Valley in Malawi., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-507, https://doi.org/10.5194/egusphere-egu2020-507, 2019.
Trogrlić, R., Wright, G., Adeloye, A., Duncan, M., and Mwale, F.: Community based-flood risk management: experiences and challenges in Malawi, Conference: XVI World Water Congress, 29 May–3 June, Abstract number 173, Cancun, Mexico, 2017.
UNDRR: Global Assessment Report on Disaster Risk Reduction, United Nation office of Disaster Risk Reduction, Geneva, 2019.
van den Homberg, M. and Susha, I.: Characterizing Data Ecosystems to Support Official Statistics with Open Mapping Data for Reporting on Sustainable Development Goals, ISPRS Int. J. Geo-Inf., 7, 456, https://doi.org/10.3390/ijgi7120456, 2018.
van den Homberg, M. J. C., Wilbrink, J., Crince, A., Kersbergen, D., Gumbi, G., Tembo, S., and Lemmens, R.: Combining UAV Imagery, Volunteered Geographic Information, and Field Survey Data to Improve Characterization of Rural Water Points in Malawi, ISPRS Int. J. Geo-Inf., 9, 592, https://doi.org/10.3390/ijgi9100592, 2020.
Wagenaar, D. J., de Bruijn, K. M., Bouwer, L. M., and de Moel, H.: Uncertainty in flood damage estimates and its potential effect on investment decisions, Nat. Hazards Earth Syst. Sci., 16, 1–14, https://doi.org/10.5194/nhess-16-1-2016, 2016.
Winter, B., Schneeberger, K., Huttenlau, M., and Stötter, J.: Sources of uncertainty in a probabilistic flood risk model, Nat. Hazards, 91, 431–446, https://doi.org/10.1007/s11069-017-3135-5, 2019.
Xu, L., Jing, W., Song, H., and Chen, G.: High-Resolution Remote Sensing Image Change Detection Combined With Pixel-Level and Object-Level, IEEE Access, 7, 78909–78918, https://doi.org/10.1109/ACCESS.2019.2922839, 2019.
Zeybek, M. and Şanlıoğlu, İ.: Point Cloud Filtering on UAV Based Point Cloud, Measurement, 133, 99–111, https://doi.org/10.1016/j.measurement.2018.10.013, 2019.
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.
This research introduces a novel approach to estimate flood damage in Malawi by applying a...
Altmetrics
Final-revised paper
Preprint