Fire, Volume 8, Issue 10 (October 2025) – 11 articles

Understanding the dynamics of fire propagation is essential in improving predictive models and developing effective fire management strategies. This study applies computer vision techniques to complement traditional fire behaviour modelling. We employ the Segment Anything Model to achieve the accurate segmentation of experimental fire videos, enabling the frame-by-frame segmentation of fire perimeters, quantification of the rate of spread in multiple directions, and explicit analysis of slope effects. Our laboratory experiments reveal that the ROS increases exponentially with slope, but with coefficients differing from those prescribed in the Canadian Fire Behaviour Prediction System, reflecting differences in field conditions. Complementary field data from prescribed burns in coniferous fuels (C-7) further demonstrate that slope effects vary under operational conditions, suggesting field-dependent dynamics not fully captured by existing deterministic models. Our experiments show that, even under controlled laboratory conditions, substantial variability in spread rate is observed, underscoring the inherent stochasticity of fire spread. Together, these findings highlight the value of vision-based perimeter extraction in generating precise spread data and reinforce the need for probabilistic modelling approaches that explicitly account for uncertainty and emergent dynamics in fire behaviour. Full article

To conduct an in-depth analysis of safety risks in small-scale business premises, this study employed field research to examine small restaurants, small supermarkets, convenience stores, and small hotels within a certain urban area. The investigation identified several critical safety issues across different types of establishments. In small restaurants, major concerns included inadequate emergency response capabilities among responsible personnel, insufficient fire separation between kitchen areas with open flames and public dining zones, as well as missing or malfunctioning emergency lighting and evacuation signage. Small supermarkets and convenience stores exhibited non-compliant electrical wiring installations and absent or defective fire extinguishing equipment. In small hotels, prevalent risks involved the lack of emergency escape respirators in guest rooms, the failure to install fire-rated doors in linen storage areas, and obstructed evacuation pathways due to clutter. Based on these findings, the study proposes practical countermeasures and recommendations aimed at enhancing safety standards in such premises. Full article

There is an urgent and constant need for land reclamation and to restore self-sustaining, stable, and resilient ecosystems. It is necessary to enhance the frequency, consistency, and success rates of applying native plant seed for ecological restoration. Smoke-water can affect seed germination of plants, regardless of whether they occur in fire-prone ecosystems. Germination trials of 18 native species of Indigenous value in the southern interior grasslands of British Columbia, Canada were conducted using a smoke aqueous solution. Locally sourced parent plant material was burned to produce smoke-water. Seeds were collected from multiple populations of the species across a wide geographic range within the B.C. southern interior to increase the genetic diversity of the seed stock. Seeds were soaked in smoke aqueous solution in various concentrates, including 0% (control), 1% (1:100), 10% (1:10), 20% (1:5), and 100%. The results indicate that germination rates in the presence of smoke-water are species-specific. Five species showed an increase in germination with smoke-water (Erythronium grandiflorum, Calochortus macrocarpus, Arnica latifolia, Lomatium nudicaule, and Shepherdia canadensis); four species showed no change (Rosa woodsii, Crataegus douglasii, Lewisia rediviva, and Prunus virginiana); and nine species showed some level of decrease (Fritillaria affinis, Fritillaria pudica, Berberis aquifolium, Claytonia lanceolata, Gaillardia aristate, Balsamorhiza sagittata, Allium cernuum, Amelanchier alnifolia, and Lomatium macrocarpum). Smoke-water also affected germination rate by plant form (herbs > shrubs), plant phenology (spring ephemeral and protracted > summer quiescent and summer mature) and plant dispersal mechanism (wind > animal). The treatments applied to encourage the germination of seeds from interior grassland forbs and shrubs have demonstrated that smoke-water can effectively break dormancy and enhance the germination rate from certain native plant species. Full article

Soundproof enclosures are essential components in ultra-high voltage converter transformer equipment. However, conventional designs pose considerable fire risks, as they may impede fire suppression efforts in case of equipment failure. This study adopted a multi-technique experimental strategy to systematically evaluate the influence of flexibilizer content on the thermal and combustion properties of soundproof enclosures. The methodology combined scanning electron microscopy and thermogravimetric analysis, cone calorimetry and thermal deformation tests. Subsequently, the entropy method was applied to quantify comprehensive fire risk based on the experimental data. The results showed that incorporation of a flexibilizer reduced thermal stability, evidenced by a decrease in the initial pyrolysis temperature from 570 K to 505–545 K at a heating rate of 5 K/min. As flexibilizer content increased, the activation energy (E_α) exhibited a pattern of initial decrease, followed by an increase, and then a subsequent decrease, with most samples exhibiting Eα values below 250 kJ/mol. Simultaneously, flexibilizer addition improved critical fire safety parameters, including reduced heat release rate, total heat release, smoke production, CO₂ release rate, mass loss rate, thermal deformation temperatures, and increased CO release rate. The comprehensive fire risk score decreased significantly from 0.2801 to a range of 0.1147–0.2522 after the addition of the flexibilizer. Thus, this study provides a quantitative assessment of fire safety in ultra-high voltage converter transformer equipment through risk evaluation, offering valuable insights for developing safer enclosure materials. Full article

Forest fire risk assessment methodologies vary considerably, presenting challenges for adaptation to specific local contexts. This study provides a systematic analysis of forest fire assessment approaches across the Mediterranean basin, American, African, and Asian regions through a comprehensive review of 112 peer-reviewed studies published from 2015 to 2025. Statistical significance testing (Chi-square tests, p < 0.05) confirmed significant regional variation in methodological preferences and indicator usage patterns. Key findings revealed that Multi-Criteria Decision Analysis dominates the field (44% of studies, n = 49), with Analytical Hierarchical Process being the most utilized method (39 studies). Machine learning approaches represent 25% (n = 28), with Random Forest leading significantly (22 applications). The analysis identified 67 indicators across seven major categories, with topographic factors (slope: 105 studies) and anthropogenic indicators (road networks: 92 studies) showing statistically significantly highest usage rates (p < 0.001), representing a statistically significant critical gap in vulnerability assessment (p < 0.01). Organizational factors remain severely underrepresented (a maximum of 14 studies for any factor), representing a statistically significant critical gap in risk assessments (p < 0.01). Statistical analysis revealed that while Mediterranean approaches excel in integrating historical and cultural factors, American methods emphasize advanced technology integration, while Asian approaches focus on socio-economic dynamics and land-use interactions. This study serves as a foundation for developing tailored assessment frameworks that combine remote sensing analysis, ground-based surveys, and community input while accounting for local constraints in data availability and technical capacity. The study concludes that effective forest fire risk assessment requires a balanced integration of global best practices with local environmental, social, and technical considerations, offering a roadmap for future forest fire risk assessment approaches in different regions worldwide. Full article

The assessment of the economic vulnerability of natural disasters is a necessary step in the evaluation of any risks. This study proposes the approach implemented under the H2020 FirEurisk project to value the economic damage of wildfires on a European scale. Economic damage is assessed as the net value change in natural (agricultural and forestry resources and their ecosystem services) and manufactured assets under simulated fire intensity, taking into consideration the time necessary for natural capital to recover to the pre-damaged conditions. We show minimum, maximum, and average damage for European countries and map the critical areas. Damages to provisioning-ecosystem services are more pronounced in Central Europe because of the lower resilience of ecosystems compared to the Mediterranean, suggesting that mitigation measures (such as managing vegetation to reduce fuel; improving access to fire services; and engaging communities through education, agriculture, and forest management participation) must be enforced. We are confident that the approach proposed may stimulate further research to test the goodness of the estimates proposed and suggest where it is more appropriate to invest in fire prevention. Full article

Modular Integrated Construction (MiC) has been strongly promoted in many dense urban areas, including the Greater Bay Area. There might be an explosion risk if leaked flammable clean refrigerants accumulate in a confined unit. Experimental and modeling studies on the explosion of flammable refrigerant propane in an MiC unit were carried out with a rectangular unit model to explore well-covered or partially covered conditions, representing the scenario of an MiC unit with its door open or closed. The experimental results were used in developing an analytical model to predict the flame surface and pressure change, with acceptable results. This study could be used as a reference for estimating pressure changes and designing ventilation systems to prevent deflagration in MiC units. 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

Wildfires pose a regularly increasing threat to ecosystems and critical infrastructure. The severity of this threat is steadily increasing. The growing threat necessitates the development of technologies for rapid and accurate early detection. However, the prevailing fire point detection algorithms, including several deep learning models, are generally constrained by the inherent hard threshold limitations in their decision-making logic. As a result, these methods lack adaptability and robustness in complex and dynamic real-world scenarios. To address this challenge, the present paper proposes an innovative two-stage, semi-supervised anomaly detection framework. The framework initially employs a Transformer-based autoencoder, which serves to transform raw fire-free time-series data derived from satellite imagery into a multidimensional deep anomaly feature vector. Self-supervised learning achieves this transformation by incorporating both reconstruction error and latent space distance. In the subsequent stage, a semi-supervised XGBoost classifier, trained using an iterative pseudo-labeling strategy, learns and constructs an adaptive nonlinear decision boundary in this high-dimensional anomaly feature space to achieve the final fire point judgment. In a thorough validation process involving multiple real-world fire cases in Yunnan Province, China, the framework attained an F1 score of 0.88, signifying a performance enhancement exceeding 30% in comparison to conventional deep learning baseline models that employ fixed thresholds. The experimental results demonstrate that by decoupling feature learning from classification decision-making and introducing an adaptive decision mechanism, this framework provides a more robust and scalable new paradigm for constructing next-generation high-precision, high-efficiency wildfire monitoring and early warning systems. Full article

In this study, a McKenna burner made for calibration is used to generate the laminar flame with the equivalence ratio of 0.78~2.0. The effect of the downward water mist spray on the extinction of the methane–air premixed laminar flame is investigated using hydroxide planar laser-induced fluorescence (OH-PLIF). The variation of the water flow rate for flame extinction is analyzed by the hydroxyl radical concentration distribution and the effective water mist flow rate. The required water flow rate for flame extinction is higher in the cases of rich fuel mixtures. The maximum critical extinguishing water flow rate for the methane–air premixed laminar flame is about 9.55 L/min under the conditions of water mist spray with a 45° solid cone spray angle and a 24 μm droplet size. Furthermore, the evolution of OH-PLIF flame behavior revealed that the stability of the hydroxyl radical concentration at the base of the flame mainly contributed to the flame extinction. This study provides a theoretical reference for the critical extinguishing conditions of water mist in the application of an active fire suppression system. Full article

This study develops, implements, and evaluates the Firebrand Spotting parameterization within the WRF-Fire coupled fire–atmosphere modeling system. Fire spotting is an important mechanism characterizing fire spread in wind-driven events. It can accelerate the rate of spread and enable the fire to spread over streams and barriers such as highways. Without the capability to simulate fire spotting, wind-driven fire simulations cannot accurately represent fire behavior. In the Firebrand Spotting parameterization, firebrands are generated with a set of fixed properties, from locations vertically aligned with the leading fire line. Firebrands are transported using a Lagrangian framework accounting for particle burnout (combustion) through an MPI-compatible implementation within WRF-Fire. Fire spots may occur when firebrands land on unburned grid points. The parameterization is verified through idealized simulations and its application is demonstrated for the 2021 Marshall Fire, Colorado. The simulations are assessed using the observed fire perimeter and time of arrival at multiple locations identified from social media footage and official documents. All simulations using a range of ignition thresholds outperform the control without spotting. Simulations accounting for fire spots show more accurate fire arrival times (i.e., reflecting a better fire rate of spread), despite producing a generally larger fire area. The Heidke Skill Score (Cohen’s Kappa) for the burn area ranges between 0.62 and 0.78 for simulations with fire spots compared to 0.47 for the control. These results show that the parameterization consistently improves the fire forecast verification metrics, while also underscoring future work priorities, including advancing the generation and ignition components. Full article