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1. 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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2. Using Structure Location Data to Map the Wildland–Urban Interface in Montana, USA

   https://doi.org/10.3390/fire5050129  

   Ketchpaw, Alexander R.; Li, Dapeng; Khan, Shahid Nawaz; Jiang, Yuhan; Li, Yingru; Zhang, Ling (October 2022, Fire)

   The increasing wildfire activity and rapid population growth in the wildland–urban interface (WUI) have made more Americans exposed to wildfire risk. WUI mapping plays a significant role in wildfire management. This study used the Microsoft building footprint (MBF) and the Montana address/structure framework datasets to map the WUI in Montana. A systematic comparison of the following three types of WUI was performed: the WUI maps derived from the Montana address/structure framework dataset (WUI-P), the WUI maps derived from the MBF dataset (WUI-S), and the Radeloff WUI map derived from census data (WUI-Z). The results show that WUI-S and WUI-P are greater than WUI-Z in the WUI area. Moreover, WUI-S has more WUI area than WUI-P due to the inclusion of all structures rather than just address points. Spatial analysis revealed clusters of high percentage WUI area in western Montana and low percentage WUI area in eastern Montana, which is likely related to a combination of factors including topography and population density. A web GIS application was also developed to facilitate the dissemination of the resulting WUI maps and allow visual comparison between the three WUI types. This study demonstrated that the MBF can be a useful resource for mapping the WUI and could be used in place of a national address point dataset. 

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3. 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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4. Simulating Potential Impacts of Fuel Treatments on Fire Behavior and Evacuation Time of the 2018 Camp Fire in Northern California

   https://doi.org/10.3390/fire5020037  

   Seto, Daisuke; Jones, Charles; Trugman, Anna T.; Varga, Kevin; Plantinga, Andrew J.; Carvalho, Leila M.; Thompson, Callum; Gellman, Jacob; Daum, Kristofer (April 2022, Fire)

   Fuel break effectiveness in wildland-urban interface (WUI) is not well understood during downslope wind-driven fires even though various fuel treatments are conducted across the western United States. The aim of this paper is to examine the efficacy of WUI fuel breaks under the influence of strong winds and dry fuels, using the 2018 Camp Fire as a case study. The operational fire growth model Prometheus was used to show: (1) downstream impacts of 200 m and 400 m wide WUI fuel breaks on fire behavior and evacuation time gain; (2) how the downstream fire behavior was affected by the width and fuel conditions of the WUI fuel breaks; and (3) the impacts of background wind speeds on the efficacy of WUI fuel breaks. Our results indicate that WUI fuel breaks may slow wildfire spread rates by dispersing the primary advancing fire front into multiple fronts of lower intensity on the downstream edge of the fuel break. However, fuel break width mattered. We found that the lateral fire spread and burned area were reduced downstream of the 400 m wide WUI fuel break more effectively than the 200 m fuel break. Further sensitivity tests showed that wind speed at the time of ignition influenced fire behavior and efficacy of management interventions. 

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5. Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

   https://doi.org/10.3390/rs13091693  

   Badola, Anushree; Panda, Santosh K.; Roberts, Dar A.; Waigl, Christine F.; Bhatt, Uma S.; Smith, Christopher W.; Jandt, Randi R. (May 2021, Remote Sensing)

   null (Ed.)

   Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest. 

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