Search Results (192)

Wildfire activity is intensifying under climate change, particularly in temperate East Asia where human-driven ignitions interact with extreme fire-weather conditions. This study examines wildfire risk during the March 2025 large wildfire event in Korea by applying explainable machine-learning models to assess ignition-prone environments and their spatial relationship with socio-environmental features relevant to exposure and management. CatBoost and LightGBM models were used to estimate wildfire susceptibility based on climatic, topographic, vegetation, and anthropogenic predictors, with SHAP analysis employed to interpret variable contributions. Both models showed strong predictive performance (CatBoost AUC = 0.910; LightGBM AUC = 0.907). Temperature, relative humidity, and wind speed emerged as the dominant climatic drivers, with ignition probability increasing under hot (>25 °C), dry (<25%), and windy (>6 m s⁻¹) conditions. Anthropogenic factors—including proximity to graves, mountain trails, forest roads, and contiguous coniferous stands (≥30 ha)—were consistently associated with elevated ignition likelihood, reflecting the role of human accessibility within pine-dominated landscapes. The socio-environmental overlay analysis further indicated that high-susceptibility zones were spatially aligned with arboreta, private commercial forests, and campsites, highlighting areas where ignition-prone environments coincide with active human use and forest management. These results suggest that wildfire risk in Korea is shaped by the spatial concurrence of climatic extremes, fuel continuity, and socio-environmental exposure. By situating explainable susceptibility modeling within an event-conditioned risk perspective, this study provides practical insights for identifying Wildfire Priority Management Areas (WPMAs) and supporting risk-informed prevention, preparedness, and spatial decision-making under ongoing climate change. Full article

The island of Gran Canaria (Spain) has undergone a significant transformation in wildfire dynamics over the past two decades, characterized by a decline in wildfire frequency but a marked increase in the severity and spatial impact of extreme events, particularly within the wildland–urban interface (WUI). This study analyzes wildfire activity between 2000 and 2020 using official datasets and statistical trend analyses, incorporating robust severity indicators and measures of burned area concentration. Results show a statistically significant decreasing trend in the number of wildfires, while burned area is extremely concentrated in a small number of high-intensity events, with four large wildfires accounting for more than 97% of the total affected area. Climatic influences on wildfire activity were assessed through the analysis of long-term meteorological indicators, focusing on trends in extreme heat days and precipitation as proxies for thermal stress and fuel moisture availability. The results indicate a substantial modification of the background climatic framework under which wildfires develop, although no direct causal relationships are inferred. In parallel, territorial processes—such as rural abandonment, increased fuel continuity, and the expansion of dispersed housing beyond consolidated settlements—act as key amplifiers of wildfire risk. Overall, the findings highlight a transition from emergency-oriented fire suppression toward resilience-based wildfire management, emphasizing the need to integrate climate adaptation, territorial planning, and stricter land-use regulation in WUI areas. Full article

In January 2025, multiple wildfires erupted across the Los Angeles region, fueled by prolonged dry conditions and intense Santa Ana winds. Southern California has faced increasingly frequent and severe wildfires in recent years, driven by prolonged drought, high temperatures, and the expanding wildland–urban interface. These fires have caused major loss of life, extensive property damage, mass evacuations, and severe air-quality decline in this densely populated, high-risk region. This study integrates passive and active satellite observations to characterize the spatiotemporal and vertical distribution of wildfire emissions and assesses their impact on air quality. TROPOMI (Sentinel-5P) and the recently launched TEMPO geostationary instrument provide hourly high temporal-resolution mapping of trace gases, including nitrogen dioxide (NO₂), carbon monoxide (CO), formaldehyde (HCHO), and aerosols. Vertical column densities of NO₂ and HCHO reached 40 and 25 Pmolec/cm², respectively, representing more than a 250% increase compared to background climatological levels in fire-affected zones. TEMPO’s unique high-frequency observations captured strong diurnal variability and secondary photochemical production, offering unprecedented insights into plume evolution on sub-daily scales. ATLID (EarthCARE) lidar profiling identified smoke layers concentrated between 1 and 3 km altitude, with optical properties characteristic of fresh biomass burning and depolarization ratios indicating mixed particle morphology. Vertical profiling capability was critical for distinguishing transported smoke from boundary-layer pollution and assessing radiative impacts. These findings highlight the value of combined passive–active satellite measurements in capturing wildfire plumes and the need for integrated monitoring as wildfire risk grows under climate change. Full article

Wildfires increasingly threaten Mediterranean landscapes, particularly in regions like Attica, Greece, where urban sprawl, agricultural abandonment, and climatic conditions heighten the risk at the Wildland–Urban Interface (WUI). The Mediterranean basin, recognized as one of the global wildfire “hotspots”, has witnessed a steady increase in both fire severity, frequency, and burned area during the last four decades, a trend amplified by urban sprawl and agricultural land abandonment. This study represents the first integrated, region-wide mapping of the WUI and associated wildfire risk in Attica, the most densely urbanized area in Greece and one of the most fire-exposed metropolitan regions in Southern Europe, utilizing advanced techniques such as Earth Observation and GIS analysis. For this purpose, various geospatial datasets were coupled, including Copernicus High Resolution Layers, multi-decadal Landsat fire history archive, UCR-STAR building footprints, and CORINE Land Cover, among others. The research delineated WUI zones into 40 interface and intermix categories, revealing that WUI encompasses 26.29% of Attica, predominantly in shrub-dominated areas. An analysis of fire frequency history from 1983 to 2023 indicated that approximately 102,366 hectares have been affected by wildfires. Risk assessments indicate that moderate hazard zones are most prevalent, covering 36.85% of the region, while approximately 25% of Attica is classified as moderate, high, or very high susceptibility zones. The integrated risk map indicates that 37.74% of Attica is situated in high- and very high-risk zones, principally concentrated in peri-urban areas. These findings underscore Attica’s designation as one of the most fire-prone metropolitan regions in Southern Europe and offer a viable methodology for enhancing land-use planning, fuel management, and civil protection efforts. Full article

Biological invasions are major threats to global biodiversity, and mapping their distribution is essential to prioritizing management efforts. The Pinaceae family (hereafter pines) includes invasive trees, particularly in Southern Hemisphere regions where they are non-native. These invasions can increase the severity of fires in wildland–urban interfaces (WUIs). We mapped pine invasion in the Bariloche WUI (≈150,000 ha, northwest Patagonia, Argentina) using supervised land cover classification of Sentinel-2 imagery with a Random Forest algorithm on Google Earth Engine, achieving 90% overall accuracy but underestimating the pine invasion area by about 25%. We then assessed in which main vegetation context pine invasions occurred relying on major vegetation units across the precipitation gradient of our study area. Invasions cover 2% of the study area, mainly in forests (61%), steppes (25.4%), and shrublands (13.4%). Most invaded areas (89.1%) are on private land; nearly 70% are on large properties (>10 ha), where state financial incentives could support removal. Another 13.5% occur on many small properties (<1 ha), where awareness campaigns could enable decentralized, low-effort control. Our land cover map can be developed further to integrate invasion dynamics, inform fire risk and behavior models, optimize management actions, and guide territorial planning. Overall, it provides a valuable tool for targeted, scale-appropriate strategies to mitigate ecological and fire-related impacts of invasive pines. Full article

Wildfires in the Wildland–Urban Interface (WUI) pose escalating threats to socio-ecological systems, challenging regional resilience and sustainable recovery. Understanding the compound impacts of such fires requires an integrated, data-driven assessment of both ecological disturbance and social response. This study develops a multi-dimensional framework combining multisource remote sensing data (Landsat/Sentinel-2 NDVI and VIIRS nighttime light) with socio-structural indicators. A Composite Disturbance Index (ImpactIndex) was constructed to quantify ecological, population, and socioeconomic disruption across six fire clusters in the January 2025 Southern California wildfires. Mechanism analysis was conducted using Fixed-Effects OLS (M2) and Geographically Weighted Regression (GWR, M3) models. The ImpactIndex revealed that Eaton and Palisades experienced the most severe compound disturbances, while Border 2 showed purely ecological impacts. During-disaster CNLI signals were statistically decoupled from ecological disturbance (ΔNDVI) and dominated by site-specific effects (p < 0.001). GWR results (Adj. R² = 0.354) confirmed asymmetric spatial heterogeneity: high-density clusters (Palisades, Kenneth) exhibited a significant “Structural Burden” effect, whereas low-density areas showed weak, nonsignificant recovery trends. This “Index-to-Mechanism” framework redefines the interpretation of nighttime light in disaster contexts and provides a robust, spatially explicit tool for targeted WUI resilience planning and post-fire recovery management. Full article

We present a site-agnostic workflow to identify Fireline Tactical Support Points (FTSPs) and corridors following wildfire where spectral-change proxies (dNBR, RdNBR, and dNDVI) are paired pre/post-fire and co-registered on a 20 m grid together with a 72 h rainfall accumulation layer, which is treated as an operational feasibility and safety overlay, complementing access and terrain. Applied to the Vesuvius National Park (Italy) wildfire episode of August 2025, the pipeline yields suitability/susceptibility surfaces, ranked factors, and corridor candidates, with estimated successes including coherent prioritization within high-severity mosaics, improved continuity toward existing access routes, and reduced overlap with mapped sensitive areas at like-for-like suitability. Low-carbon staging is retained as a design safeguard, while detailed greenhouse-gas accounting is intentionally deferred to future, fleet-resolved multi-criteria analyses. The approach enables rapid, repeatable decision support and is relevant to SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

In Chile, human activity is a key factor in the occurrence and impact of wildfires in the wildland–urban interface, as more than 95% of such events are anthropogenic in origin. The 2024 Valparaíso megafire represents the most severe incident in the past three decades, with significant consequences for both the affected population and local infrastructure. In disaster contexts, the media play a crucial role in shaping social representations by establishing analytical categories within society. Therefore, the objective of this paper is to describe how Chilean media outlets addressed this megafire during the wildfire management process, considering the agenda during the whole wildfire season in Chile. The methodological approach is based on a multi-stage strategy for news classification based on the wildfire lifecycle: prevention (before), response (during), and recovery (after). We have employed a mixed-method design that integrates manual and computational techniques (topic analysis) as a triangulation technique on the same social network data. This study automatically collects articles related to the Valparaiso megafire, which occurred in 2024, from 140 Chilean media sources, considering print, radio, and television media. The main finding indicates that news coverage predominantly frames the Valparaiso megafire as a particular event in a short period of time. The media coverage does not focus on wildfire concepts such as nature, state management, policy, and the relationship between state and citizen. Finally, the automated analysis of emerging topics in the articles belonging to each manual category provides a consistent description of the social representations identified through manual analysis. Full article

Burned area, fire severity, and suppression expenditures have increased in British Columbia in recent decades with climate change. Approximately 80% of suppression expenditures are attributable to wildfires near the Wildland–Urban Interface (WUI). Evaluating the potential for fuel management to reduce suppression expenditures is essential to mitigating demands on fire response resources and reducing impacts on communities. One management approach is to increase the proportion of deciduous tree species, which have a lower propensity for crown fire. Using fire suppression expenditure data from 1981 to 2014, we applied the machine learning method causal forests (CFs) to estimate the effect of the proportion of conifer forest cover on suppression expenditures for WUI fires and how these effects varied with other influential factors (i.e., heterogenous treatment effects). Across all fires, the effect of conifer cover on suppression expenditures was stronger on private land compared to public land, under high fire danger measured by daily severity ratings (DSRs), which reflect wind speed and fuel moisture, and for fires igniting earlier in the calendar year, based on Julian day. These findings provide insights into prioritizing wildland fuel treatment when budgets are limited. The CFs approach demonstrates potential for broader applications in fire risk mitigation and analysis beyond the scope of the current data. CFs may also be valuable in other areas of forest research where heterogenous treatment effects are common. Full article

The increasing frequency and intensity of wildfires pose severe risks to ecosystems, infrastructure, and human safety. In wildland–urban interface (WUI) areas, nearby vegetation strongly influences building ignition risk through flame contact and radiant heat exposure. However, limited research has leveraged Unmanned Aerial Systems (UAS) remote sensing (RS) to capture species-specific vegetation geometry and predict thermal responses during ignition events This study proposes a two-stage framework integrating UAS-based multispectral (MS) imagery, LiDAR data, and Fire Dynamics Simulator (FDS) modeling to estimate the maximum temperature (T) and heat flux (HF) of outdoor vegetation, focusing on Syzygium smithii (Lilly Pilly). The study data was collected at a plant nursery at Queensland, Australia. A total of 72 commercially available outdoor vegetation samples were classified into 11 classes based on pixel counts. In the first stage, ensemble learning and watershed segmentation were employed to segment target vegetation patches. Vegetation UAS-LiDAR point cloud delineation was performed using Raycloudtools, then projected onto a 2D raster to generate instance ID maps. The delineated point clouds associated with the target vegetation were filtered using georeferenced vegetation patches. In the second stage, cone-shaped synthetic models of Lilly Pilly were simulated in FDS, and the resulting data from the sensor grid placed near the vegetation in the simulation environment were used to train an XGBoost model to predict T and HF based on vegetation height (H) and crown diameter (D). The point cloud delineation successfully extracted all Lilly Pilly vegetation within the test region. The thermal response prediction model demonstrated high accuracy, achieving an RMSE of 0.0547 °C and R² of 0.9971 for T, and an RMSE of 0.1372 kW/m² with an R² of 0.9933 for HF. This study demonstrates the framework’s feasibility using a single vegetation species under controlled ignition simulation conditions and establishes a scalable foundation for extending its applicability to diverse vegetation types and environmental conditions. Full article

Conventional wildfire assessment products emphasize regional-scale ignition likelihood and potential spread derived from fuels and weather. While useful for broad planning, they do not directly support boundary-aware, scenario-specific decision-making for localized threats to communities in the Wildland–Urban Interface (WUI). This limitation constrains the ability of fire managers to effectively prioritize mitigation efforts and response strategies for ignition events that may lead to severe local impacts. This paper introduces WUI-BTI—a scenario-based, simulation-driven boundary-threat index for the Wildland–Urban Interface that quantifies consequences conditional on an ignition under standardized meteorology, rather than estimating risk. WUI-BTI evaluates ignition locations—referred to as Fire Amplification Sites (FAS)—based on their potential to compromise the defined boundary of a community. For each ignition location, a high-resolution fire spread simulation is conducted. The resulting fire perimeter dynamics are analyzed to extract three key metrics: (1) the minimum distance of fire approach to the community boundary ($D_{min}$) for non-breaching fires; and for breaching fires, (2) the time required for the fire to reach the boundary ($T_p$), and (3) the total length of the community boundary affected by the fire ($L_c$). These raw outputs are mapped through monotone, sigmoid-based transformations to yield a single, interpretable score: breaching fires are scored by the product of an inverse-time urgency term and an extent term, whereas non-breaching fires are scored by proximity alone. The result is a continuous boundary-threat surface that ranks ignition sites by their potential to rapidly and substantially compromise a community boundary. By converting complex simulation outputs into scenario-specific, boundary-aware intelligence, WUI-BTI provides a transparent, quantitative basis for prioritizing fuel treatments, pre-positioning suppression resources, and guiding protective strategies in the WUI for fire managers, land use planners, and emergency response agencies. The framework complements regional hazard layers (e.g., severity classifications) by resolving fine-scale, consequence-focused priorities for specific communities. Full article

Mongolia’s rapidly expanding capital is encroaching on Bogd Khan Mountain, a UNESCO Biosphere Reserve and the oldest protected area in Eurasia. Gray wolves (Canis lupus) in this wildland–urban interface are locally near-threatened due to hunting, local beliefs, and human–wildlife conflict. In 2022 and 2023, we deployed 72 camera traps (11,539 trap nights) to investigate how wolves respond to overlapping pressures from free-ranging dogs, livestock, and human activity. Using a random habitat-stratified camera design and abundance modeling, we assessed diel activity and spatial co-occurrence. Wolves exhibited nocturnal and crepuscular activity, with the greatest temporal overlap with wild prey (wapiti: ∆⁴ = 0.73; Siberian roe deer: ∆⁴ = 0.79), moderate overlap with dogs (∆⁴ = 0.60) and horses (∆⁴ = 0.68), and minimal overlap with cattle (∆⁴ = 0.40) and people (∆⁴ = 0.43). Mean wolf abundance estimates ranged from λ = 0.91 (CI 95%, 0.05–1.77) in 2022 to λ = 1.52 (CI 95%, 0.44–3.53) in 2023. Wolves were more abundant at higher relative abundance of wild ungulates and in areas with more people. Wolves co-occurred with dogs at 11 sites and were more abundant in areas with a higher number of dogs. Our findings highlight the complex dynamics between wildlife, livestock, and human-associated disturbances at the wildland–urban interface, underscoring the need for integrated management strategies that address both ecological and human dimensions of conservation. Full article

Wildfire activity is intensifying globally as climate change amplifies heat waves, droughts and wind extremes, threatening biodiversity. South Korea (63% forested) has experienced a sharp rise in large fires. We analysed 905 wildfires ≥ 5 ha from 1980–2024, linking burned area to maximum wind speed, relative humidity, temperature and forest structure (conifer, broadleaf and mature–stand ratios, forest cover). Pearson correlations, HC3-corrected regression, a 1000-tree Random Forest and five-fold validated XGBoost interpreted with SHAP captured linear and nonlinear effects; WUI influences were examined qualitatively. Each 1 m s⁻¹ increase in peak wind expanded burned area by ~8.5 ha, whereas a 1% rise in humidity reduced area by ~3 ha (p < 0.01). Broadleaf prevalence restrained spread, while high conifer and mature–stand proportions enlarged it. Machine learning raised explanatory power from R² = 0.62 to 0.66 and showed that very dry air, strong winds and conifer cover above half the landscape coincided with the largest events. Burned area during 2020–2024 reached 29,905 ha—sevenfold that of 2015–2019. These results imply that extreme fire weather, flammable pine fuels and expanding WUI settlements jointly elevate risk; implementing real-time meteorological thresholds, targeted fuel treatments and stricter WUI zoning can help mitigate this risk. Full article

This study investigates the elemental composition of magnetic nanoparticles (MNPs) in eleven wildland–urban interface (WUI) fire ashes, including one vegetation, six structural, and four vehicle ashes, along with three fire-impacted soil samples. The WUI fire ash samples were collected following the 2020 North Complex (NC) Fire and Sonoma–Lake–Napa unit (LNU) Lightning Complex Fire in California. Efficiency of magnetic separation was confirmed via Time-Domain Nuclear Magnetic Resonance (TD-NMR); the relaxometry showed that the transverse relaxation rate R₂ decreased from 2.02 s⁻¹ before separation to 0.29 s⁻¹ after separation (ΔR₂ = −1.73 s⁻¹; −86%), due to the removal of magnetic particles. The particle number concentrations, size distributions, and elemental compositions (and ratios) of MNPs were determined using single particle-inductively coupled plasma–time-of-flight-mass spectrometry (SP-ICP-TOF-MS). The major types of nanoparticles (NPs) detected in the magnetically separated MNPs were Fe-, Ti-, Cr-, Pb-, Mn-, and Zn-bearing NPs. The iron-bearing NPs accounted for 3.2 to 83.5% of the magnetically separated MNPs, and decreased following the order vegetation ash (77.4%) > soil (63.2–69.9%) > structural (3.2–83.5%) ash. The titanium-bearing NPs accounted for 3.3 to 66.1% of the magnetically separated MNPs, and decreased following the order vehicle (14.1–66.1%) > structural (3.5–36.4%) > vegetation (3.3%) ash. The majority of the detected NPs in the fire ashes occurred in the form of multi-metal (mm) NPs, attributed to the presence of NPs as heteroaggregates and/or due to the sorption of metals on the surfaces of NPs during combustion. However, a notable fraction (3–91%) of the detected NPs occurred as single-metal (sm) NPs, particularly smFe-bearing NPs, which accounted for 48 to 91% of all the Fe-bearing particles in the magnetically separated MNPs. The elemental ratios (e.g., Al/Fe, Ti/Fe, Cr/Fe, and Zn/Fe) in the magnetically separated MNPs from structural and vehicle ashes were higher than those in the soil samples and vegetation ashes, indicating enrichment of metals in magnetically separated NPs from vehicle and structural ashes compared to vegetation ash. Overall, this study demonstrates that the MNPs generated by WUI fire ash are associated with potentially toxic elements (e.g., Cr and Zn), exacerbating the environmental and human health risks of WUI fires. This study also highlights the need for further research into the properties, environmental fate, transport, and interactions of MNPs with biological systems during and following WUI fires. Full article

A major fire occurred in the wildland–urban interface in southern Portugal, on 13 July 2022, becoming uncontrolled due to weather conditions. This study investigates how atmospheric dynamics increased fire danger in Mainland Portugal during early July 2022. The synoptic circulation from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and mesoscale conditions from Meso-NH model simulation at 1.5 km resolution revealed atmospheric conditions before and during the fire. Fire risk was assessed using the Fire Weather Index (FWI) from Meso-NH outputs. A blocking pattern was configured by an upper-level low-pressure system in early July, remaining semi-stationary west of Mainland Portugal until 18 July. The counter-clockwise circulation of the cut-off low resulted in dry, warm air advection from North Africa, enhancing fire danger over the Iberian Peninsula. In southern Portugal, a jet-like wind with strong east/southeasterly flow from Gibraltar Strait favored rapid fire spread. This circulation below 1 km altitude from the Mediterranean Sea enhanced fire danger through strong winds, independent of the large-scale blocking pattern. This study presents an atmospheric scenario for evaluating fire danger in Southern Portugal, important for pre-firefighting management that complemented previous studies for the region. Also, high-resolution FWI calculations using Meso-NH emphasized the importance of improved temporal and spatial resolution for fire danger assessment. Full article