Wildland Urban Interface Areas Research Articles

Global expansion of wildland-urban interface intensifies human exposure to wildfire risk in the 21st century.

Rapidly increasing human-nature interactions exacerbate the risk of exposure to wildfires for human society. The wildland-urban interface (WUI) represents the nexus of human-nature interactions, where the risk of exposure to natural hazards such as wildfire is most pronounced. However, quantifying long-term global WUI change and the corresponding driving factors at fine resolution remain challenging. Here, we mapped and analyzed the global WUI at 30-meter resolution in 2000, 2010, and 2020. Our analysis revealed that the global WUI expanded by 35.6% since 2000, reaching 1.93 million square kilometer in 2020. Notably, 85% of this growth occurred between 2010 and 2020. The increase in WUI was primarily driven by the unprecedented expansion of global urbanization, contributing an additional 589,914 square kilometer of WUI. In addition, the number of small fires occurring in WUI areas has increased substantially since 2010. These findings underscore the rising wildfire risk to human society and highlight the urgency of implementing tailored fire management strategies in WUI areas.

The economic and environmental impact of fire preventive strategies in the Mediterranean region

Fire behaviour in the Mediterranean region has been altered by climate change. In the last decade, not only has the occurrence of fires increased but also their virulence. This is primarily due to higher temperatures and the decrease in the rainfall, which have made forest ecosystems less able to withstand fires. It has also been observed that most wildfires are related directly or indirectly with human actions, and they usually occur in wildland-urban interface (WUI) areas. The current research focuses on the economic quantification of the benefits that fire preventive strategies could generate, demonstrating that it is worth it to invest in this kind of measures for both the environment and the society. This study shows the results of a pioneering project, called GUARDIAN, which is applied in a WUI area located at the east of Spain, with the aim of preventing and combating wildfires that could put at risk the life of 15,000 inhabitants while preserving the Natural Park of Túria and La Vallesa (Valencia-Spain). GUARDIAN is a multifaceted project that integrates recycled water, advanced technology, and ecological enhancements to create a more fire-resilient environment while educating and preparing the local community for fire-related challenges. The results of the current research intend to give a value to those benefits of the project that usually have not a market value and are difficult to measure, and due to that fact, they are not usually considered in the cost-benefit analysis. The methodology applied allows to compare in economic terms the environmental benefits of fire preventive measures implemented in the GUARDIAN project with the costs incurred by the measures developed. The environmental area protected by the project results in a value that ranges between €338,035,481 to €485,384,281. Accordingly, the methodology and results of this study are of great interest to public administrations, encouraging the implementation of fire preventive strategies.

Urban forest cover and ecosystem service response to fire varies across California communities

Urban fires that result from wildfires are an emerging, extreme event affecting communities and urban forests globally. However, much of the fire effects on urban ecosystems literature is primarily focused on Wildland-Urban Interface (WUI) areas, correlates of building loss, risk mitigation, and wildland vegetation and fuels. Three recent urban fires in California USA provided an opportunity to explore these effects on urban forests: the 2017 Tubbs (Santa Rosa) and Thomas (Ventura) and the 2018 Camp fire that burned Paradise. Accordingly, we analyzed pre- and post-fire neighborhood level urban tree cover (nUTC) change over 5 years using Sentinel and LiDAR data (10m resolution). Then, we explored the effects of fire severity on changes in several regulating ecosystem services (e.g., carbon, air pollution, stormwater). Findings from the Rapid Assessment of Vegetation Condition after Wildfire severity processes and other geospatial datasets show that fire effects were patchy with fire severity within neighborhoods ranging from unburned to extreme. We found that ~5 years after the fires, and relative to adjacent non-fire affected neighborhoods, Ventura and Santa Rosa’s nUTC is recovering to pre-fire levels while Paradise’s nUTC is being consistently lost over time. Ventura and Santa Rosa had 20-25% of their fire affected area outside established WUI boundaries. However, local-scale urban tree cover and ecosystem service supply are lagged, and recovery time depends on the surrounding biome and socio-ecological context. In inland, higher elevation communities – like Paradise – the recovery of nUTC and the associated ecosystem services might materialize over a much longer timeframe. Our study provides a roadmap to assess the response of urban wildfire-affected tree cover and ecosystem services across space and time. It is also one of the first assessments of fire effects on urban ecosystems and communities outside of WUI boundaries that are now experiencing increased threat from wildfires globally.

Presence of asbestos in building materials and soils in postfire areas of Mati, Kineta and Varimbombi in Greece.

The present study was carried out to determine the presence of asbestos in Wildland Urban Interface (WUI) areas of Attica, Greece affected by wildfires between 2018 and 2021. It concerns the first major campaign that took place in Greece. The samples tested in this work were collected from prespecified buildings of the burned area. The samples included different types of building materials such as bricks, wall coatings, insulation plates etc. Soil samples nearby the buildings were also collected to examine dispersion of the fibers. The identification of asbestos was based on the optical properties of the fibrous particles and was performed with stereo microscope and Polarized Light Microscopy according to P401 provided by BOHS (Health and Safety Executive (HSE) 2021). Scanning Electron Microscopy with energy dispersive spectroscopy was also used to validate the presence of asbestos and determine its chemical composition. In this work, 2 different types of asbestos were determined, chrysotile and crocidolite. In some cases, fragments of asbestos containing materials were also detected in the afore-mentioned soil samples indicating dispersion of asbestos containing debris in an area around the burned spots. The presence of asbestos that was identified in this preliminary study could raise concerns to humans in the urban areas. For that reason, a risk assessment for the identified asbestos containing materials (ACMs) was conducted according to the guidelines on management and abatement of ACMs of Health and Safety Authority and the Asbestos: Survey guide, Appendix 4: Material assessment algorithm of Health and Safety Executive (HSE).

Next-gen regional fire risk mapping: Integrating hyperspectral imagery and National Forest Inventory data to identify hot-spot wildland-urban interfaces

The increasing threat of high-severity wildfires in Mediterranean Wildland-Urban Interface (WUI) areas demands to develop effective fire risk assessment and management strategies. Simultaneously, the newfound accessibility of spaceborne hyperspectral data represents a significant potential for generating fire severity assessments, whereas National Forest Inventories (NFI) offer a vast dataset related to vegetation and fuel loads, which is essential for shaping the planning and strategies of forest services. This research work aims to advance the state-of-the-art in WUI fire risk mapping in the western Mediterranean Basin by combining PRISMA spaceborne hyperspectral data and Spanish NFI data. The proposed methodology had three main stages: (i) fire severity assessment at local scale (a wildfire) by using PRISMA hyperspectral data and Multi-Endmember Spectral Mixture Analysis (MESMA) leveraging field-based measurements of the Composite Burn Index (70 plots); (ii) development of a high fire severity probability map at regional scale from the extrapolation of a Random Forest predictive model calibrated from fire severity estimates, NFI data and topo-climatic variables at local scale (overall accuracy = 92 %; Kappa = 0.8); and (iii) identification and characterization of zones that concentrate WUIs with high probability of high fire severity if a fire event occurs (hot-spot WUIs) by crossing the information from the previous regional high fire severity probability map and a WUI cartography developed at regional scale. Study area was Castilla y León Autonomous Region (larger Spanish region, 94,226 km2), where the second-largest extreme Spanish wildfire event (28,000 ha) occurred. We identified hot-spot WUIs so that stakeholders and decision-makers could (i) prioritize resources and interventions for effective fire management and mitigation, (ii) allocate resources for prevention, and (iii) plan evacuation measures to safeguard lives and property. This study contributes to the development of next-generation fire risk assessment methods that combine remote sensing technologies with comprehensive ground-level datasets.

Modelling the vulnerability of urban settings to wildland–urban interface fires in Chile

Abstract. Wildland–urban interface (WUI) regions are particularly vulnerable to wildfires due to their proximity to both nature and urban developments, posing significant risks to lives and property. To enhance our understanding of the risk profiles in WUI areas, we analysed seven fire case studies in central Chile. We developed a mixed-method approach for conducting local-scale analyses, which involved field surveys, remote-sensing through satellite and drone imagery, and GIS-based analysis of the collected data. The methodology led to the generation of a georeferenced dataset of damaged and undamaged dwellings, including 16 variables representing their physical characteristics, spatial arrangement, and the availability of fire suppression resources. A binary classification model was then used to assess the relative importance of these attributes as indicators of vulnerability. The analysis revealed that spatial arrangement factors have a greater impact on damage prediction than the structural conditions and fire preparedness of individual units. Specifically, factors such as dwelling proximity to neighbours, distance to vegetation, proximity to the border of dwelling groups, and distance from the origin of the fire substantially contribute to the prediction of fire damage. Other structural attributes associated with less affluent homes may also increase the likelihood of damage, although further data are required for confirmation. This study provides insights for the design, planning, and governance of WUI areas in Chile, aiding the development of risk mitigation strategies for both built structures and the broader territorial area.

Remapping California's wildland urban interface: A property-level time-space framework, 2000–2020

Wildland fire poses a significant risk to property and people, and these risks tend to be highest in places where flammable, wildland vegetation abuts urban development. Traditionally, efforts to map these areas of intersection, known as the Wildland Urban Interface (WUI), have relied on satellite-derived land cover and census data. While these types of data are valuable for broadly delineating WUI areas, they are constrained in their ability to specifically identify at-risk residential properties and their characteristics over time. This article addresses these challenges through a multi-time-step, property-level framework that enhances current approaches based on moving window mapping, the Time Step Moving Window (TSMW) framework. We implement this framework on approximately 10 million geo-located property records from Zillow's Transaction and Assessment Database for California. Using this framework, we generate estimates of California's WUI from 2000 to 2020 and find that our time stepped building scale maps have allowed us to classify residential homes at-risk to burns with greater accuracy compared to time stepped Census polygon based maps. Based on these maps, we further estimate that approximately $1.34 Trillion, or 40%, of California's improved residential property value is situated within the WUI. Our approach provides a high-precision strategy for delineating at-risk residences and calculating localized financial costs associated with future hazard events.

Global expansion of wildland-urban interface (WUI) and WUI fires: insights from a multiyear worldwide unified database (WUWUI)

Fires in the wildland-urban interface (WUI) are an important issue globally. To understand the change of WUI, we develop a 9 km worldwide unified wildland-urban interface database for 2001–2020 with Random Forest models and satellite data. We find that WUI has been increasing in all populated continents from 2001 to 2020 and the global relative increase is 24%, with the largest relative increase (∼59%) over Africa. Global total fire counts decrease by 10% from 2005 to 2020, whereas the WUI fraction of fire counts increases by 23%. The global total burned area decreases by 22% from 2005 to 2020, whereas the WUI fraction of burned area increases by 35%. These are mainly due to the expansion of WUI area. On all the populated continents, the WUI fractions of fire counts are higher than the WUI fractions of burned area, implying that WUI fires tend to have smaller sizes than wildland fires. We also project future WUI changes for the years 2030 and 2040, together with the projection of future fire burned area under different shared socioeconomic pathways (SSP) scenarios in the Community Earth System Model version 2 (CESM2). The projected global WUI fraction (excluding Antarctica and the oceans) is 5.9% in 2040 compared to 4.8% in 2020. The global WUI fraction of burned area is projected to increase from now to 2040 under most scenarios analyzed in this study, unless the WUI area stays at the 2020 level together with the projected burned area under SSP4-4.5. This study is a first step to understanding the changes of WUI fires at the global scale and demonstrates a growing importance of WUI fires. The global multi-year WUI and WUI fire datasets developed in this study can facilitate future work quantifying the impacts of WUI fires on air quality and climate.

Assessing the Accuracy of the Wildland–Urban Interface Index in Portuguese Rural Villages’ Context: A Case Study of the 2017 Pedrógão Grande Wildfire

Climate change and human interventions can boost wildfires. Although naturally happening, massive events are becoming more frequent and severe. In Portugal’s mainland, many rural settlements are populated mainly by older people, and uninhabited houses are frequently poorly conserved. This combination leaves the Wildland–Urban Interface (WUI) dangerously exposed to the fires. Pursuing the understanding of WUI areas, this study applies the Wildland–Urban Interface Index (WUIX) assessment methodology to an area severely affected by the massive 2017 wildfire of Pedrógão Grande, Leiria, Portugal. The primary objective of this study was to compare the results from WUIX with the areas burned during the fire event. As a result, maps of WUI effect were generated, visually pointing to villages with higher severity compared to the others. A statistical analysis was performed in three villages from the region to validate the results by comparing the accuracy of the results obtained to the actual damages. The results point out a high correlation between the WUIX and the real scenario despite the apparent challenges in determining the variations in different types of fire effect. Finally, the WUIX results align with the data from the Pedrógão Grande wildfire, showing that some are promising in conjunction with other wildfire indicators.

Evaluating the long-term effects of near-natural restoration on post-fire forest dynamics in a wildland-urban interface landscape

Forests in the wildland-urban interface (WUI) are of high value but vulnerable to wildland fires due to abundant fire ignitions and flammable forest fuels. Restoring the post-fire Wildland-Urban Interface (WUI) forest landscape is of utmost importance in order to maintain ecosystem service provision. The near-natural restoration strategy is widely employed in vegetation restoration as it enables the formation of healthy, stable, and diverse artificial mixed forests that resemble natural forests. To evaluate the long-term effects of near-natural restoration on the WUI forest landscape, which are largely unclear, we used a wildfire in 2019 near Shenyang City in northeast China as an example and investigated the post-fire forest dynamics under two different scenarios (i.e., natural succession and near-natural restoration) based on the forest landscape model. The results demonstrated that near-natural restoration can significantly accelerate the restoration process in terms of forest biomass, species biodiversity, and age structure. Under the near-natural restoration scenario, the biomass of the burned area can be quickly restored within 20 years after the fire. At the species level, the biomass and proportion of pioneer tree species such as Pinus tabuliformis and Robinia pseudoacacia decreased under the near-natural restoration scenario, while other species started to increase. Then post-fire near-natural planting accelerated the restoration of forest biodiversity, by 2070, the Shannon–Wiener index was predicted to be 1.49 under natural succession and remained at 2.02 under near-natural restoration. In terms of age structure, near-natural restoration shortens the recovery time of fire trails to mature forests. In summary, near-natural restoration accelerates forest recovery in post-fire WUI areas. Our results highlighted the impact of near-natural restoration on forest conservation to inform post-fire forest planning and management practices.

The wildland-urban interface and the relationship with wildfires in the municipalities of Campina Grande do Sul and Quatro Barras, Paraná, Brazil

Campina Grande do Sul and Quatro Barras are two Brazilian municipalities with extensive vegetative areas with social interaction and, in addition, suffer from the presence of wildfires. The aim was to delimit the wildland-urban interface for these municipalities, relating to the occurrence of wildfires, to serve as a subsidy for preventive and vegetation fire-fighting policies. It used a methodology for classifying wildland-urban interface areas, already established globally, based on the density of households and forest cover. Two methodologies from the Brazilian Institute of Geography and Statistics were used to obtain the density of households. When the statistical grid was used, Campina Grande do Sul presented a wildland-urban interface coverage of 12.5% ​​and Quatro Barras 13.6%. In the use of census sectors, Campina Grande do Sul presented 25.7% and Quatro Barras 13.6%. The statistical grid presented greater detail than use of the census sectors. The presence of fires in areas with a wildland-urban interface demonstrates the need for preventive policies to be applied to the habitants of these places. It is recommended to continue studies, as well as to create or adapt methodologies for classifying the wildland-urban interface based on local characteristics.

Modeling Wildland Firefighters’ Assessments of Structure Defensibility

In wildland–urban interface areas, firefighters balance wildfire suppression and structure protection. These tasks are often performed under resource limitations, especially when many structures are at risk. To address this problem, wildland firefighters employ a process called “structure triage” to prioritize structure protection based on perceived defensibility. Using a dataset containing triage assessments of thousands of structures within the Western US, we developed a machine learning model that can improve the understanding of factors contributing to assessed structure defensibility. Our random forest models utilized variables collected by wildland firefighters, including structural characteristics and the surrounding ignition zone. The models also used landscape variables not contained within the triage dataset that captured important information about accessibility, vegetation, topography, and structure density. We achieved a high overall accuracy (77.8%) in classifying structures as defensible or non-defensible. The presence of a safety zone was the most important factor in determining structure defensibility. Road proximity, vegetation composition, and topography were also found to have high importance. In addition to improving the understanding of factors considered by wildland firefighters, communities could also gain from this information by enhancing their wildfire response plans, focusing on targeted mitigation, and improving their overall preparedness.

A forest fire hazard model and map for a wildland urban interface not meteorologically prone to forest fires

Fire Hazard (FH) modelling is a relevant fire prevention/assessment tool. This work proposes a FH model and generates a FH map for a wildland urban interface area in Germany that is not prone to extreme fires. The main input data include weather, topography, fuel, and anthropic-related potential ignition points. The main steps include (1) identification/description of weather scenarios, and for each scenario (2) analysis of potential fire ignition through simulation of Fire Probability (FP), (3) modelling the potential fire behaviour through simulation of Fireline Intensity (FLI), (4) generation of a FH map by combining FP and FLI maps, and (5) integration of all maps into a final FH map. Extreme ignition and propagation conditions were considered: (1) a fuel model that describes the fire performance in an extreme drought scenario, (2) the human influence through mechanistic ignitions, and (3) the worst case of all scenarios. As results, four weather scenarios were identified and described. FP maps, FLI maps, and FH maps were created for each of them, and finally an integrated FH map (IFHM) was derived.

Assessing Fire Risk in Wildland–Urban Interface Regions Using a Machine Learning Method and GIS data: The Example of Istanbul’s European Side

Like many places around the world, the wildland–urban interface areas surrounding urban regions are subject to variable levels of fire risk, threatening the natural habitats they contact. This risk has been assessed by various authors using many different methods and numerical models. Among these approaches, machine learning models have been successfully applied to determine the weights of criteria in risk assessment and risk prediction studies. In Istanbul, data have been collected for areas that are yet to be urbanized but are foreseen to be at risk using geographic information systems (GIS) and remote sensing technologies based on fires that occurred between 2000 and 2021. Here, the land use/land cover (LULC) characteristics of the region were examined, and machine learning techniques, including random forest (RF), extreme gradient boosting (XGB), and light gradient boosting (LGB) models, were applied to classify the factors that affect fires. The RF model yielded the best results, with an accuracy of 0.70, an F1 score of 0.71, and an area under the curve (AUC) value of 0.76. In the RF model, the grouping between factors that initiate fires and factors that influence the spread of fires was distinct, and this distinction was also somewhat observable in the other two models. Risk scores were generated through the multiplication of the variable importance values of the factors and their respective layer values, culminating in a risk map for the region. The distribution of risk is in alignment with the number of fires that have previously occurred, and the risk in wildland–urban interface areas was found to be significantly higher than the risk in wildland areas alone.

Evaluating driving behavior patterns during wildfire evacuations in wildland-urban interface zones using connected vehicles data

Wildfire risk is increasing all over the world, particularly in the western United States and the communities in wildland-urban interface (WUI) areas are at the greatest risk of fire. Understanding the driving behavior of individuals to evacuate fire-affected WUI areas is important as the evacuees may encounter low visibility and difficult driving conditions due to burning material and steep topography. This study investigates the driving behavior patterns of individuals during historical wildfire events in rural and urban areas with mandatory evacuation orders using a connected vehicle dataset. This dataset provides the geolocation and timestamp of vehicles’ hard-braking (HB) and hard-acceleration (HA) events. The comparative analysis of the data demonstrated that the reported HA & HB event patterns were consistent in representing the varying driving behavior in response to the changing driving conditions and the depiction of the temporal and spatial impact of the fire in all studied areas. Moreover, the HB event dataset located critical traffic congestion points and the HA event dataset revealed the hurried response of evacuees on the exiting routes as a result of short-notice evacuation. In addition, significant differences in driving behavior patterns were noticed between rural and urban areas.

A geographically flexible approach for mapping the Wildland-Urban Interface integrating fire activity data

The Wildland-Urban Interface (WUI) is the area where houses and natural vegetation meet or intermingle. WUI areas are exposed to an increased hazard of wildfires and have significantly expanded worldwide in the past few decades. In this study, we developed a new empirical approach for mapping the WUI by generating a WUI index based on the juxtaposition among buildings, vegetation, and the fire history of the study area. We first calculated the percentage coverage of buildings and three different fuel typologies within circular moving windows with radii of 100, 250, and 500 m, and then acquired the fire history data between 2012 and 2021 for Israel and the West Bank (Palestinian Authority) from the VIIRS active fires remote sensing product. We defined the WUI as cells where the combination of vegetation cover and building cover had more VIIRS fire detections than expected by chance. To assess the effects of using broad vs. local scale parameterizations on resulting WUI maps, we repeated this process twice, first using national-scale data, and then separately in four distinct geographic regions. We assessed the congruence in the amounts and patterns of WUI in regions as mapped by information from these two analysis scales. We found that the WUI in Israel and the West Bank ranged from 0.5% to 1.7%, depending on fuel type and moving window radius. The scale of parameterization (national vs. regional) affected the WUI patterns only in one of the regions, whose characteristics differed markedly than the rest of the country. Our new method differs from existing WUI mapping methods as it is empirical and geographically flexible. These two traits allow it to robustly map the WUI in other countries with different settlement, fuel, climate and wildfire characteristics.

Fires at the wildland-industrial interface. Is there an emerging problem?

Over the past years, wildfires have raged with unprecedented intensity across the world, becoming a growing problem, as weather conditions conductive to wildfire ignition and spread will increase in frequency and severity worldwide. This, coupled with a growing human expansion, leads to an increase in wildfire risk and in the threat to wildland-urban interface (WUI) communities. Commonly, definitions for WUI areas consider homes, commercial facilities, office and public buildings. This excludes industrial installations, where wildfires can trigger accidents or cascading events leading to extremely dangerous situations for the population causing enormous economic losses. In this paper, the problem associated to the wildland-industrial interface (WII) is analyzed. A methodology to obtain a global WII map is described, and the first WII maps for Europe and Asia are provided. Results show that, in Europe, 2.5% of the land and 6% of vegetated areas are WII, while in Asia these are respectively 0.24% and 0.5%. An analysis of how wildfire triggered industrial accidents can be considered when performing quantitative risk assessments (QRA) in industrial sites is also performed, identifying the current state of the art and research gaps, with the aim of helping industry, public authorities and policy makers, for better accident prevention, preparedness and response.

Local community participation and volunteerism in wildfire area management: A systematic review

Wildfires have caused considerable economic, ecological, and social damage in recent years. For this reason, decision-makers in wildfire management (WFM) have face increasingly difficult challenges. While decision support systems help decision-makers, it is clear that some deficiencies still persist. In this context, it is thought that the active role of local people involved in wildfire management can eliminate these deficiencies because they have experience and direct knowledge about fighting wildfires in Wildland Urban Interface (WUI) areas. Hence, their expertise can be utilized in future wildfire containment efforts. In this study, the author presents some general information about WUI, public participation, and the decision-making process and its relation to wildfires. In addition, the author will also examine previous studies on the participation of local people in wildfire management and investigate the decision-making processes regarding this issue by using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique. The results of this study suggest that there should be a widespread adoption of the community-based integrated fire management (CBIFM) approach, instead of the top-down management approach commonly employed in wildfire management. The results strongly suggest that decision-makers should reach a consensus as to how the principle of participation in fire management should work by reviewing the socio-economic interests of the local community.

Is critical infrastructure safe from wildfires? A case study of wildland-industrial and -urban interface areas in South Korea

Global climate change, global warming, and unplanned urbanization have resulted in industrial facilities and livelihoods encroaching on wildlands. Wildfire risks concerns about natural hazards triggering technological accidents (Natech) caused by wildfires in wildland-industrial and -urban interface areas are globally increasing. As wildfires that could trigger Natech accidents occur infrequently but often with unpredicted and uncontrollable consequences, critical infrastructure and industrial facilities should prepare for the potential catastrophic impact of wildfires beforehand. This paper describes a case study of wildfire-threatened critical energy infrastructure located in wildland-industrial interface (WII) and wildland-urban interface (WUI) areas in South Korea. The energy infrastructure avoided a serious Natech accident through intensive risk and emergency management. Although there was no Natech disaster or dreadful damage to the energy facility, this threat to the energy infrastructure is a reminder to prepare for future Natech disasters in WII and WUI areas that could result in unmanageable consequences. This study highlights the need for intensive and integrated wildfire-specific Natech risk management, considering critical infrastructure and industrial facilities in WII and WUI areas, that should include all stakeholders with local residents and enhance Natech resilience.

Assessment of vegetation regrowth and spatial patterns and severity factors of wildfires in wildland-urban interface - the case of the large wildfire in Baião (2019)

Portugal is one of the countries most affected by forest fires in southern Europe, with recurrent events and frequent impacts. The demographic and social changes that have occurred in rural areas have driven land neglect in recent years, which, in turn, influences forest management and wildland-urban interface (WUI) areas that are related to fires. Therefore, it is the aim of this study to develop a case study in the municipality of Baião, based on the large wildfire (LWF) of 2019, defining and mapping the WUI areas, as well as evaluate, the recurrence, the GIF severity and in a period of 2 years, the regeneration of vegetation, in areas with different land uses and affected by different severities. The study was organized into 4 stages, being that in the first proceeded to the mapping of fire occurrences, the second of the wildland-urban interfaces, the third the characterization of the recurrence of large fires, the fourth corresponded to the evaluation of the severity of the large wildfire of 2019 and the evaluation of the vegetation regeneration, as a function of land use. The WUI represent 26.7% of the territory of the municipality of Baião, during the years 2001 to 2021 the municipality registered 3 770 fire occurrences. The LWF of Baião burned an area corresponding to 853 ha, the burned area in 2019 presented a maximum number of 12 fires between the years of 1975 to 2019, resulting in a maximum degree of 11 recurrences for the same area. We can verify that 2 years after the LWF, the area occupied by forest and scrub classes, which were hit by high severity, already showed significant levels of vegetation regeneration. With this, the main conclusions consider studies in this line contribute to the understanding of the patterns created by the wildfire in different landscapes, being information valuable for forest managers to understand the consequences (beneficial or not) and plan actions of prevention, restoration, and environmental education.