Structural Vulnerability Assessment of Residential Buildings to Windstorm Hazard with Impact Analysis on Forest Stands: A Case Study from Vojvodina, Serbia
DOI:
https://doi.org/10.66050/nhg50f24Keywords:
hazards, vulnerability assessment, windstorm disaster, hazard, image analysis, forest, buildingsAbstract
This study presents an indicator-based methodology for assessing the structural vulnerability of individual residential buildings to windstorm hazard. The methodology is based on the Household Sector Approach: CIMDEN 2001 procedure, with parameters adapted to assess the vulnerability of an individual house to windstorm events. In the case of a windstorm event, the structural vulnerability of a house is analyzed through five parameters with assigned weights: roof type, roof construction, roof sides, roof material, number of floors, and doors and windows on non-roof sides. The further classification into low, medium, and high classes is based on construction material and building type, recognizing that some are more vulnerable than others. The material classification is based on the analysis of historical windstorm event outcomes and on material and building types used in specific regions of interest (in this work, Vojvodina, an autonomous province in Serbia). The material and building types in this region are similar across the whole Pannonian Basin. During the development of this methodology, the authors also incorporated the indigenous knowledge and experience of structural damage consequences from two recent supercell storm events on 19 and 21 July 2023. that heavily hit the Novi Sad metropolitan area and caused disruption and destruction of forest areas near the Danube River, power lines, and roofs on schools, individual houses, residential buildings, and companies. The methodology was applied to 50 houses in Bačka Palanka and 11 houses in Begeč, both of which were affected by severe supercell windstorms on 19 and 21 July 2023. Building attributes were derived from Google Street View imagery (2014) and field survey (2026). The resulting vulnerability assessment enabled spatial visualization and comparative assessment in a GIS environment. Buildings with lightweight roof structures, unsealed edges, and multiple openings exhibited higher vulnerability scores, whereas massive masonry structures with sealed roof systems showed greater resistance. Direct windstorm impacts on adjacent riparian forest stands were assessed using Sentinel-2 NDVI change detection, identifying 173.87 ha of severe canopy loss. Beyond immediate damage, the study outlines potential cascading socioecological effects in which household recovery needs may increase pressure on forest ecosystem services.
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1. Cvetković, V., Tanasić, J., Ocal, A., Kešetović, Ž., Nikolić, N., & Dragašević, A. (2021). Capacity development of local self-governments for disaster risk management. International Journal of Environmental Research and Public Health, 18(19), 10406. https://doi.org/10.3390/ijerph181910406
2. Enderami, S. A., Mazumder, R. K., & Sutley, E. J. (2022). Framework for incorporating community social vulnerability in the assessment of hurricane-induced wind risk to residential buildings. 14th Americas Conference on Wind Engineering, Lubbock, Texas, United States. https://doi.org/10.48550/arXiv.2207.14206
3. García-Jácome, S. P., Jankovský, M., Hoeben, A. D., Lindner, M., Uzquiano, S., Stern, T., Nuhlíček, O., Vuletić, D., Marjanović, H., Picos, J., Peltoniemi, M., Baumbach, L., & Lloret, F. (2025). Forest value chain resilience from a local perspective in five European countries: Analysis of predictors and co-drivers. Frontiers in Forests and Global Change, 7, 1461932. https://doi.org/10.3389/ffgc.2024.1461932
4. Gardiner, B., Schuck, A., Schelhaas, M.-J., Orazio, C., Blennow, K., & Nicoll, B. (Eds.). (2013). Living with storm damage to forests. European Forest Institute. https://doi.org/10.13140/2.1.1730.2400
5. Ibrahim, H. A., Elawady, A., & Prevatt, D. O. (2024). Structural performance and fragility assessment of elevated residential buildings during 2017–2018 hurricanes in Texas and Florida. Journal of Building Engineering, 90, 109393. https://doi.org/10.1016/j.jobe.2024.109393
6. Jeftic, L., & Knezevic, J. (2024). Supercell storm induced forest windfall disaster. MIRCE Akademy. https://doi.org/10.13140/RG.2.2.21249.2672
7. Jonikavičius, D., & Mozgeris, G. (2013). Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data. iForest, 6, 150–155. https://doi.org/10.3832/ifor0715-006
8. Khanduri, A. C., & Morrow, G. C. (2003). Vulnerability of buildings to windstorms and insurance loss estimation. Journal of Wind Engineering and Industrial Aerodynamics, 91, 455–467. https://doi.org/10.1016/S0167-6105(02)00408-7
9. Massarra, C., Friedland, C., & Akhnoukh, A. (2021). Development of wind and flood vulnerability index for residential buildings. In Design and construction of smart cities (pp. 151–159). Springer. https://doi.org/10.1007/978-3-030-64217-4_18
10. Mehdizadeh, R., Deck, O., Pottier, N., & Péné-Annette, A. (2023). Post-disaster reconstruction of residential buildings: Evolution of structural vulnerability on Caribbean Island of Saint Martin after Hurricane Irma. Sustainability, 15, 12788. https://doi.org/10.3390/su151712788
11. Milenković, D., Cvetković, V., Beriša, H., Jakovljević, V., Gačić, J., & Cvetković, V. (2026). Beyond the original BRIC model: Gaps, limitations, and adaptation of community resilience indicators for local contexts. International Journal of Disaster Risk Management, 8(1), 55–76.
12. Moos, C., Dietrich, K., Erbach, A., Ginzler, C., Noyer, E., Schaller, C., & Dorren, L. (2025). Recovery of the forest’s protective effect after stand-replacing wind disturbances. Scientific Reports, 15, 19727. https://doi.org/10.1038/s41598-025-03090-9
13. Pap, P., Vasić, V., Poljaković Pajnik, L., Drekić, M., Marković, M., Zlatković, M., & Stojanović, D. V. (2022). Windstorms in poplar clones plantations in Vojvodina Province. Topola, 210, 65–72. https://doi.org/10.5937/topola2210065P
14. Papathoma-Köhle, M., Ghazanfari, A., Mariacher, R., Huber, W., Lücksmann, T., & Fuchs, S. (2023). Vulnerability of buildings to meteorological hazards: A web-based application using an indicator-based approach. Applied Sciences, 13, 6253. https://doi.org/10.3390/app13106253
15. Perez, I. (2001). Personal communication.
16. Rahman, M. M., Sarker, S., Biswas, A., Roy, S., & Mahmud, M. A. (2025). Exploring flood-induced livelihood vulnerabilities in Bangladesh: Insights from Teota, Manikganj and the Bangladesh Delta Plan 2100. International Journal of Disaster Risk Management, 7(2), 333–360. https://doi.org/10.18485/ijdrm.2025.7.2.18
17. Romagnoli, F., Cadei, A., Costa, M., Marangon, D., Pellegrini, G., Nardi, D., Masiero, M., Secco, L., Grigolato, S., Lingua, E., Picco, L., Pirotti, F., Battisti, A., Locatelli, T., Blennow, K., Gardiner, B., & Cavalli, R. (2023). Windstorm impacts on European forest-related systems: An interdisciplinary perspective. Forest Ecology and Management, 541, 121048. https://doi.org/10.1016/j.foreco.2023.121048
18. Romagnoli, F., Masiero, M., & Secco, L. (2022). Windstorm impacts on forest-related socio-ecological systems: An analysis from a socio-economic and institutional perspective. Forests, 13, 939. https://doi.org/10.3390/f13060939
19. Roof Gnome. (n.d.). 15 types of roof styles. https://roofgnome.com/blog/roofing/types-of-roof-styles/
20. Roy, B. K., Shawon, M. I. H., & Hasan, M. M. (2025). Community-driven risk assessment: Integrating local perceptions into quantifiable risk weights using Analytical Hierarchy Process (AHP)-Geographical Information System (GIS). International Journal of Disaster Risk Management, 7(2), 131–152. https://doi.org/10.18485/ijdrm.2025.7.2.8
21. Stojanović, D. B., Orlović, S., Zlatković, M., Kostić, S., Vasić, V., Miletić, B., Kesić, L., Matović, B., Božanić, D., Pavlović, L., Milović, M., Pekeč, S., & Đurđević, V. (2021). Climate change within Serbian forests: Current state and future perspectives. Topola, 208, 39–56. https://doi.org/10.5937/topola2108039S
22. Thywissen, K. (2006). Components of risk: A comparative glossary. United Nations University, Institute for Environment and Human Security.
23. Tomppo, E., Ronoud, G., Antropov, O., Hytönen, H., & Praks, J. (2021). Detection of forest windstorm damages with multitemporal SAR data—A case study: Finland. Remote Sensing, 13, 383. https://doi.org/10.3390/rs13030383
24. Trojand, A., Rust, H. W., & Ulbrich, U. (2025). Temporal dynamic vulnerability: Impact of antecedent events on residential building losses to wind storm events in Germany. Natural Hazards and Earth System Sciences, 25, 2331–2350. https://doi.org/10.5194/nhess-25-2331-2025
25. United Nations Office for Disaster Risk Reduction. (2017). The Sendai Framework terminology on disaster risk reduction: Disaster risk. https://www.undrr.org/terminology/disaster-risk
26. Villagrán, J. C. (2004). Manual para la estimación de riesgos asociados a diversas amenazas. Acción Contra el Hambre.
27. Villagrán, J. C. (2005). Quantitative vulnerability and risk assessment in communities on the foothills of Pacaya Volcano in Guatemala. Journal of Human Security and Development, 1(1), 1–25.
28. Villagrán, J. C. (2006). Vulnerability: A conceptual and methodological review. United Nations University, Institute for Environment and Human Security.
29. Višacki, V., Pavlović, L., Stojnić, S., Stojanović, D. B., Kesić, L., Turšijan, L., & Orlović, S. (2024). The impact of windbreaks on vegetation indices of field crops. Topola, 214, 59–72. https://doi.org/10.5937/topola2414059V
30. Walker, G. R. (2011). Modelling the vulnerability of buildings to wind: A review. Canadian Journal of Civil Engineering, 38. https://doi.org/10.1139/L11-047.
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Copyright (c) 2026 Lazar Jeftic, Vladimir Višacki, Srdjan Stojnić, Dejan B. Stojanovic, Lazar Kesić, Bratislav Matović, Saša Orlović (Author)

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