Articles | Volume 24, issue 4
https://doi.org/10.5194/nhess-24-1521-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-24-1521-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 May 2024
Research article |
| 02 May 2024
| 02 May 2024
Modelling the vulnerability of urban settings to wildland–urban interface fires in Chile
Instituto de Ingeniería Matemática y Computacional, Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
Jorge León
Departamento de Arquitectura, Universidad Técnica Federico Santa María, Valparaíso, Chile
Constanza González-Mathiesen
Facultad de Arquitectura y Arte, Universidad del Desarrollo, Concepción, Chile
Randy Román
Research Center for Integrated Disaster Risk Management (CIGIDEN), Santiago, Chile
Manuela Penas
Centro de Investigación de Vulnerabilidades e Informalidades Territoriales, Facultad de Arquitectura y Ciencias Sociales, Universidad de Valparaíso, Valparaíso, Chile
Alonso Ogueda
Department of Mathematical Sciences, George Mason University, Fairfax, VA, USA
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Cited
19 citations as recorded by crossref.
- Synoptic and Regional Meteorological Drivers of a Wildfire in the Wildland–Urban Interface of Faro (Portugal) F. Couto et al. https://doi.org/10.3390/fire8090362
- La interfaz urbano-forestal como tierra de nadie en la construcción del riesgo de incendio forestal en ciudades costeras chilenas E. Jaque-Castillo et al. https://doi.org/10.22320/07183607.2025.28.52.04
- A Comparative Study of a Deep Reinforcement Learning Solution and Alternative Deep Learning Models for Wildfire Prediction C. Vidal-Silva et al. https://doi.org/10.3390/app15073990
- Land Cover and Wildfire Risk: A Multi-Buffer Spatial Analysis of the Relationship Between Housing Destruction and Land Cover in Chile’s Bío-Bío Region in 2023 B. Hora et al. https://doi.org/10.3390/su17104416
- Preface: Multi-risk assessment in the Andes region E. Schoepfer et al. https://doi.org/10.5194/nhess-25-1163-2025
- Improving Wildfire Resilience in the Mediterranean Central-South Regions of Chile F. Veloso et al. https://doi.org/10.3390/fire8060212
- Advancing Spatial Planning for Wildfire-Resilient Settlements: Insights From Chile and Victoria (Australia) C. Gonzalez-Mathiesen https://doi.org/10.1080/01944363.2025.2527117
- Predicting California Wildfire Damage to Structures Using Machine Learning: A Comparative Study of Random Forest and XGBoost A. Noumeur & M. Tohir https://doi.org/10.1088/1742-6596/3121/1/012029
- When wildfires reward incumbents: Risk exposure and electoral accountability in Chile F. Livert et al. https://doi.org/10.1016/j.ijdrr.2026.106146
- A methodology for assessing multiple hazards applied to Sweden J. Björck et al. https://doi.org/10.1016/j.ijdrr.2024.104934
- I want to help too! Information demands on Instagram during the media coverage of the 2024 Chile mega-fires C. Ortega-Gunckel https://doi.org/10.1080/10714421.2025.2545679
- Proposal for a Data Model for a Multipurpose Cadastre in Chile Based on Land Administration Model ISO 19152 for Natural Disaster and Risk Management D. Flores-Rozas & M. Manso-Callejo https://doi.org/10.3390/urbansci9120532
- Wildfire Occurrence In Chile: Regional Modeling And Implications For Risk Management R. Crespo Pérez et al. https://doi.org/10.18172/cig.6792
- Urban Fire Risk Evaluation Integrating Image Features with Interpretable Machine Learning Models Z. Li et al. https://doi.org/10.1007/s12061-025-09752-5
- Enhanced fine-scale satellite-based wildfire exposure assessment in wildland–urban interface communities using deep learning N. Shirzad-Ghaleroudkhani et al. https://doi.org/10.1071/WF24207
- Using Drones to Estimate and Reduce the Risk of Wildfire Propagation in Wildland–Urban Interfaces O. Santos & N. Santos https://doi.org/10.3390/asi8030062
- Exploring urban vegetation type and defensible space’s role in building loss during wildfire-driven events in California F. Escobedo et al. https://doi.org/10.1016/j.landurbplan.2025.105421
- Socio-ecological impacts of the 2025 Los Angeles urban fires on communities, neighborhoods, and homes C. Norlen et al. https://doi.org/10.1038/s41467-026-71376-1
- Remote sensing and spatial analysis for estimating vegetation fire risk in the Puglia Region G. Cillis et al. https://doi.org/10.3832/efor4800-022
19 citations as recorded by crossref.
- Synoptic and Regional Meteorological Drivers of a Wildfire in the Wildland–Urban Interface of Faro (Portugal) F. Couto et al. https://doi.org/10.3390/fire8090362
- La interfaz urbano-forestal como tierra de nadie en la construcción del riesgo de incendio forestal en ciudades costeras chilenas E. Jaque-Castillo et al. https://doi.org/10.22320/07183607.2025.28.52.04
- A Comparative Study of a Deep Reinforcement Learning Solution and Alternative Deep Learning Models for Wildfire Prediction C. Vidal-Silva et al. https://doi.org/10.3390/app15073990
- Land Cover and Wildfire Risk: A Multi-Buffer Spatial Analysis of the Relationship Between Housing Destruction and Land Cover in Chile’s Bío-Bío Region in 2023 B. Hora et al. https://doi.org/10.3390/su17104416
- Preface: Multi-risk assessment in the Andes region E. Schoepfer et al. https://doi.org/10.5194/nhess-25-1163-2025
- Improving Wildfire Resilience in the Mediterranean Central-South Regions of Chile F. Veloso et al. https://doi.org/10.3390/fire8060212
- Advancing Spatial Planning for Wildfire-Resilient Settlements: Insights From Chile and Victoria (Australia) C. Gonzalez-Mathiesen https://doi.org/10.1080/01944363.2025.2527117
- Predicting California Wildfire Damage to Structures Using Machine Learning: A Comparative Study of Random Forest and XGBoost A. Noumeur & M. Tohir https://doi.org/10.1088/1742-6596/3121/1/012029
- When wildfires reward incumbents: Risk exposure and electoral accountability in Chile F. Livert et al. https://doi.org/10.1016/j.ijdrr.2026.106146
- A methodology for assessing multiple hazards applied to Sweden J. Björck et al. https://doi.org/10.1016/j.ijdrr.2024.104934
- I want to help too! Information demands on Instagram during the media coverage of the 2024 Chile mega-fires C. Ortega-Gunckel https://doi.org/10.1080/10714421.2025.2545679
- Proposal for a Data Model for a Multipurpose Cadastre in Chile Based on Land Administration Model ISO 19152 for Natural Disaster and Risk Management D. Flores-Rozas & M. Manso-Callejo https://doi.org/10.3390/urbansci9120532
- Wildfire Occurrence In Chile: Regional Modeling And Implications For Risk Management R. Crespo Pérez et al. https://doi.org/10.18172/cig.6792
- Urban Fire Risk Evaluation Integrating Image Features with Interpretable Machine Learning Models Z. Li et al. https://doi.org/10.1007/s12061-025-09752-5
- Enhanced fine-scale satellite-based wildfire exposure assessment in wildland–urban interface communities using deep learning N. Shirzad-Ghaleroudkhani et al. https://doi.org/10.1071/WF24207
- Using Drones to Estimate and Reduce the Risk of Wildfire Propagation in Wildland–Urban Interfaces O. Santos & N. Santos https://doi.org/10.3390/asi8030062
- Exploring urban vegetation type and defensible space’s role in building loss during wildfire-driven events in California F. Escobedo et al. https://doi.org/10.1016/j.landurbplan.2025.105421
- Socio-ecological impacts of the 2025 Los Angeles urban fires on communities, neighborhoods, and homes C. Norlen et al. https://doi.org/10.1038/s41467-026-71376-1
- Remote sensing and spatial analysis for estimating vegetation fire risk in the Puglia Region G. Cillis et al. https://doi.org/10.3832/efor4800-022
Saved (final revised paper)
Latest update: 14 Jul 2026
Short summary
Wildfires pose a significant risk to property located in the wildland–urban interface (WUI). To assess and mitigate this risk, we need to understand which characteristics of buildings and building arrangements make them more prone to damage. We used a combination of data collection and analysis methods to study the vulnerability of dwellings in the WUI for case studies in Chile and concluded that the spatial arrangement of houses has a substantial impact on their vulnerability to wildfires.
Wildfires pose a significant risk to property located in the wildland–urban interface (WUI). To...
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