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1. Mapping the wildland-urban interface in California using remote sensing data

   https://doi.org/10.1038/s41598-022-09707-7  

   Li, Shu; Dao, Vu; Kumar, Mukesh; Nguyen, Phu; Banerjee, Tirtha (December 2022, Scientific Reports)

   Abstract Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California’s population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate the new type of datasets, we developed a threshold criteria for mapping WUI based on statistical analysis, as opposed to using more ad-hoc criteria as used in previous mapping approaches. This method removes the reliance on census data in WUI mapping, and does not require the calculation of housing density. Moreover, this approach designates the adjacent areas of each building with large and dense parcels of vegetation as WUI, which can not only refine the scope and resolution of the WUI areas to individual buildings, but also avoids zoning issues and uncertainties in housing density calculation. Besides, the new method has the capability of updating the WUI map in real-time according to the operational needs. Therefore, this method is suitable for local governments to map local WUI areas, as well as formulating detailed wildfire emergency plans, evacuation routes, and management measures. 

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2. Examining the existing definitions of wildland‐urban interface for California

   https://doi.org/10.1002/ecs2.4306  

   Kumar, Mukesh; Li, Shu; Nguyen, Phu; Banerjee, Tirtha (December 2022, Ecosphere)

   Abstract Past studies reported a drastic growth in the wildland–urban interface (WUI), the location where man‐made structures meet or overlap wildland vegetation. Fighting fire is difficult in the WUI due to the combination of wildland and structural fuels, and therefore, WUI areas are characterized by frequent damage and loss of structures from wildfires. Recent wildland fire policy has targeted fire prevention, evacuation planning, fuel treatment, and home hardening in WUI areas. Therefore, it is important to understand the occurrence of wildfire events relative to the location of the WUI. In this work, we have reported the occurrences of wildfires with respect to the WUI and quantified how much of the WUI is on complex topography in California, which intensifies fire behavior and complicates fire suppression. We have additionally analyzed the relative importance of WUI‐related parameters, such as housing density, vegetation density, and distance to wildfires, as well as topographic factors, such as slope, elevation, aspect, and surface roughness, on the occurrence of large and small wildfires and the burned area of large wildfires near the WUI. We found that a very small percentage of wildfire ignition points and large wildfire‐burned areas (>400 ha or 1000 acres) were located in the WUI areas. A small percentage of large wildfires were encountered in WUI (3%), and the WUI area accounted for only 4% of the area burned, which increased to 5% and 56%, respectively, outside WUI (5‐km buffer from WUI). Similarly, 66% of fires ignited outside WUI, whereas only 3.6% ignited within WUI. Results from this study have implications for fuel management and infrastructure hardening, as well as for fire suppression and community response. 

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3. Cluster-Based Active-Learning Scenario Reduction Framework for Probabilistic Wildfire Risk Assessment

   Jonnalagadda, J; Lee, JY; Sanad, A-A (January 2026, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering)

   Wildfires pose an escalating risk to communities and infrastructure, especially in regions undergoing increased fuel dryness and temperature extremes driven by climate change, as well as continued expansion into the wildland-urban interface (WUI). Probabilistic wildfire risk assessment provides a rigorous means of quantifying potential impacts, but its application is often hindered by the high computational cost of working with hundreds of thousands of complex wildfire scenarios. This study introduces a novel scenario reduction framework tailored to the unique characteristics of wildfire hazards, which often lack standard intensity metrics and exhibit highly nonlinear, spatially distributed behavior. The proposed framework selects a subset of scenarios that best represent the spatial and statistical diversity of the full dataset, thereby greatly reducing computational costs while accounting for uncertainties. This is achieved by mapping complex wildfire scenarios into a high-dimensional feature space, enabling similarity assessments based on spatial consequence patterns rather than standard intensity metrics. A k-medoids clustering approach is then used to identify a representative subset of scenarios, while an active-learning-based outlier selection procedure incorporates rare but high-impact events without inflating computational demands. The framework was first demonstrated using a simple illustrative example to show how its performance responds to different data characteristics. To further demonstrate the practicality of the framework, it was used for wildfire risk assessment in Spokane County, Washington, where the full dataset (1000 scenarios) was reduced to 41 representative scenarios while preserving the spatial patterns of burn probability and building damage with high fidelity. The results demonstrated that the framework significantly improves computational efficiency and accuracy compared to traditional scenario reduction methods, offering a scalable and flexible tool for probabilistic wildfire risk assessment. 

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4. Mitigation behaviors of homeowners and renters in the wildland urban interface

   https://doi.org/10.1016/j.ijdrr.2025.105688  

   Borate, A; Figueroa, OP; Houston, D; Ihinegbu, C; Jong-Levinger, A; Schubert, JE; Sanders, BF (July 2025, International journal of disaster risk reduction)

   Residential development within the wildland-urban interface (WUI) has greatly expanded in the United States since the 1990s, amplifying wildfire risk by placing people and structures in greater proximity to flammable vegetation. Household wildfire mitigation actions can vary substantially by cost, knowledge required, and perceived effectiveness, but few studies have examined them separately and how their adoption varies by housing tenure in the context of wildfires. To address this gap, we surveyed residents living in WUI areas within Southern California near recent burn scars in the Santa Ana and San Bernardino Mountain ranges. Drawing on the Protection Motivation Theory and the Theory of Planned Behavior, we evaluated the factors driving the adoption of five Wildfire Mitigation Intention or Implementation (WMII) action types: fire insurance, structural retrofits, exterior minor maintenance, exterior vegetative measures, and community actions. Findings indicate that self-efficacy (perceived ability to undertake protective measures) and response efficacy (perceived effectiveness of a protective measure) are positively associated with all action types, with self-efficacy having a stronger association. Factors associated with implementation or intention to take mitigation action differed across action types. Renters reported lower levels of mitigation overall and faced greater financial and knowledge barriers. Findings stress that wildfire mitigation programs should account for how knowledge, resources, and abilities to take different WMII actions vary by housing tenure. Findings suggest that wildfire emergency officials should focus on capacity building and public education initiatives for WUI residents, with a particular focus on addressing the unique challenges renters face in high-risk areas. 

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5. Exploring and Testing Wildfire Risk Decision-Making in the Face of Deep Uncertainty

   https://doi.org/10.3390/fire6070276  

   Johnson, Bart R.; Ager, Alan A.; Evers, Cody R.; Hulse, David W.; Nielsen-Pincus, Max; Sheehan, Timothy J.; Bolte, John P. (July 2023, Fire)

   We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland–urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within the same scenario as stochastic elements in simulated wildfire, succession, and landowner decisions create large sets of unique, path-dependent futures for analysis. We applied the modeling system to an 815 km2 study area in western Oregon at a sub-taxlot parcel grain and annual timestep, generating hundreds of alternative futures for 2007–2056 (50 years) to explore how WUI communities facing compound risks from increasing wildfire and expanding periurban development can situate and assess alternative risk management approaches in their localized SES context. The ability to link trends and uncertainties across many futures to processes and events that unfold in individual futures is central to the modeling system. By contrasting selected alternative futures, we illustrate how assessing simulated feedbacks between wildfire and other SES processes can identify tradeoffs and leverage points in fire-prone WUI landscapes. Assessments include a detailed “post-mortem” of a rare, extreme wildfire event, and uncovered, unexpected stabilizing feedbacks from treatment costs that reduced the effectiveness of agent responses to signs of increasing risk. 

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