37 citations as recorded by crossref.

1. Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study D. Rajapaksha et al. 10.3390/buildings14061864
2. Review article: Natural hazard risk assessments at the global scale P. Ward et al. 10.5194/nhess-20-1069-2020
3. Economic implications of autonomous adaptation of firms and households in a resource-rich coastal city A. Taberna et al. 10.1038/s41598-023-46318-2
4. Terrestrial and airborne laser scanning and 2-D modelling for 3-D flood hazard maps in urban areas: new opportunities and perspectives P. Costabile et al. 10.1016/j.envsoft.2020.104889
5. The Potential Role of News Media to Construct a Machine Learning Based Damage Mapping Framework G. Okada et al. 10.3390/rs13071401
6. Physical Vulnerability and Local Responses to Flood Damage in Peri-Urban Areas of Dhaka, Bangladesh M. Fatemi et al. 10.3390/su12103957
7. Measuring rising heat and flood risk along the belt-and-road initiative J. Liang et al. 10.1007/s44274-024-00148-9
8. Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem T. Johnson et al. 10.5194/nhess-24-2285-2024
9. 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
10. Developing assessment flow for damage estimation of mud housing typology through a case study against coastal floods N. Aishwarya et al. 10.1038/s41598-023-33468-6
11. Integrating agent-based approaches with flood risk models: A review and perspective J. Aerts 10.1016/j.wasec.2020.100076
12. Development of damage curves for buildings near La Rochelle during storm Xynthia based on insurance claims and hydrodynamic simulations M. Diaz Loaiza et al. 10.5194/nhess-22-345-2022
13. Developing flood vulnerability curve for rice crop using remote sensing and hydrodynamic modeling V. Hendrawan & D. Komori 10.1016/j.ijdrr.2021.102058
14. Development of flood damage assessment method for residential areas considering various house types for Bago Region of Myanmar B. Shrestha et al. 10.1016/j.ijdrr.2021.102602
15. Relationship between residential house damage and flood characteristics: A case study in the Teesta River Basin, Bangladesh S. Haque et al. 10.1016/j.ijdrr.2023.103901
16. Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia D. D'Ayala et al. 10.5194/nhess-20-2221-2020
17. Quantifying crop vulnerability to weather-related extreme events and climate change through vulnerability curves B. Monteleone et al. 10.1007/s11069-022-05791-0
18. Quantifying the potential benefits of risk-mitigation strategies on future flood losses in Kathmandu Valley, Nepal C. Mesta et al. 10.5194/nhess-23-711-2023
19. The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes M. de Ruiter et al. 10.1029/2020EF001531
20. Who Is Vulnerable and Where Do They Live? Case Study of Three Districts in the Uttarakhand Region of India Himalaya C. Grainger et al. 10.1659/MRD-JOURNAL-D-19-00041.1
21. A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai Z. Li et al. 10.3390/w14182840
22. Framework for urban flood risk assessment – a hydrological modelling approach: the case of Nilambur, Kerala A. John et al. 10.1080/13563475.2024.2427402
23. 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 L. Wouters et al. 10.5194/nhess-21-3199-2021
24. Characterizing uncertainty of general building stock exposure data C. Huyck et al. 10.1177/87552930221079852
25. Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations C. Xu et al. 10.1007/s13753-023-00524-8
26. Improved assessment of rainfall-induced railway infrastructure risk in China using empirical data W. Zhu et al. 10.1007/s11069-022-05605-3
27. Using global datasets to estimate flood exposure at the city scale: an evaluation in Addis Ababa A. Carr et al. 10.3389/fenvs.2024.1330295
28. Long‐term flood exposure assessment using satellite‐based land use change detection and inundation simulation: A 30‐year case study of the Bangkok Metropolitan Region S. Darnkachatarn & Y. Kajitani 10.1111/jfr3.12997
29. Evaluating targeted heuristics for vulnerability assessment in flood impact model chains A. Zischg et al. 10.1111/jfr3.12736
30. A generic physical vulnerability model for floods: review and concept for data-scarce regions M. Malgwi et al. 10.5194/nhess-20-2067-2020
31. Expert-based versus data-driven flood damage models: A comparative evaluation for data-scarce regions M. Malgwi et al. 10.1016/j.ijdrr.2021.102148
32. The tale of three floods: From extreme events and cascades of highs to anthropogenic floods A. Alborzi et al. 10.1016/j.wace.2022.100495
33. Does safer housing save lives? An analysis of typhoon mortality and dwellings in the Philippines S. Healey et al. 10.1016/j.ijdrr.2022.103433
34. Physical vulnerability to dynamic flooding: Vulnerability curves and vulnerability indices M. Papathoma-Köhle et al. 10.1016/j.jhydrol.2022.127501
35. Flood Protection and Land Value Creation – Not all Resilience Investments Are Created Equal P. Avner et al. 10.1007/s41885-022-00117-7
36. Integrated Flood Impact and Vulnerability Assessment Using a Multi-Sensor Earth Observation Mission with the Perspective of an Operational Service in Lombardy, Italy M. Righini et al. 10.3390/land13020140
37. Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks M. Zarekarizi et al. 10.1038/s41467-020-19188-9