Fire Ignition Research Articles

Spatial Modeling of Forest Fire Risks in A Watershed Using Remote Sensing

Objective: This study investigates remote sensing techniques for monitoring and environmental planning in areas with a higher risk of wildfires in the São Nicolau watershed, located in the municipality of São João Evangelista-MG, Brazil. Method: The research employed a quantitative approach, analyzing a 30-year historical series and incorporating nine significant variables influencing wildfire risk. The data were processed and analyzed using advanced geotechnologies, enabling the mapping of risk areas. Results and Discussion: The results indicate that the study area comprises 3.02 ha of low risk (0.13%), 3,835.66 ha of moderate risk (16.35%), 17,540.28 ha of high risk (74.79%), 2,073.87 ha of very high risk (8.84%), and 0.18 ha of extremely high risk (0.00%). These findings reveal the predominance of high-risk areas, highlighting the urgent need for mitigation measures. Wildfire risk maps represent the areas most prone to fire on a base map, integrating factors that influence fire ignition and spread. Based on this information, various measures can be implemented, such as increased surveillance in high-risk areas, restricted access, construction of preventive firebreaks, and reorganization of management practices (Ferraz & Vettorazzi, 1998). Research Implications: The findings provide valuable input for strategic planning of preventive actions against wildfires, contributing to public policies for environmental conservation and sustainable management in critical areas.

Remotely geolocating static events observed by citizens using data collected by mobile devices

The increasing use of smartphones has led to a surge in crowdsourcing initiatives, where citizens easily collect and upload information using advanced sensors, leveraging the collective efforts of the crowd. However, these devices face accuracy issues that must be addressed before they can be used effectively in certain applications. While most research has focused on GNSS-based positioning errors, compass-based orientation errors have received far less attention. This paper presents a novel method for determining the geolocation of static events by combining contributions from multiple volunteers located around a target event. Instead of straight lines, the method applies funnel-shaped regions to represent the azimuths toward the target location and encompasses various phases to address errors stemming from measured azimuths. These compass-based orientation errors have attracted less attention compared to GNSS-based positioning errors. The approach mitigates the uncertainty in azimuth measurements, producing a set of regions that contain the target location with different levels of confidence. Its reliability was tested in three case studies with known target locations, using metrics such as area and compactness. The results were promising, indicating that the developed approach is particularly useful in applications that do not require a high degree of accuracy (common in many crowdsourcing projects), such as the geolocation of forest fire ignitions − once in the vicinity they can be easily spotted. Implementing this approach within a system that collates citizens’ contributions can furnish invaluable information to authorities, empowering prompt action during emergency scenarios.

Electricity-Caused Wildland Fires: Costs, Social Fairness, and Proposed Solution

If electric power is distributed by an overhead network of cables, the ignition of wildland fires is unavoidable, although prudent management efforts can reduce the losses. The economic aspects of these fires are driven by tort litigation, which tends to create serious problems of social fairness. The present system does not contain adequate incentives towards minimizing these costs, nor appropriate measures to ensure that costs are allocated in a fair manner. The problems are universal, but a specific focus on the wildfire situation in California is assumed. The electric utilities there are regulated by the California Public Utilities Commission, and the regulations are almost wholly prescriptive. Striking is the absence of any benefit/cost considerations in the regulation of utilities. Regulations have also created distortions in the insurance market, notably subsidizing fire-unsafe behaviors. The legal and regulatory system should be changed to promote fire-safe behaviors. It should also be changed to more fairly apportion the cost burdens. A strategy which should be adopted more widely is that of Public Safety Power Shutoffs. The optimal solution is to enact legislation to create a no-fault system, similar to Workers’ Compensation. In such a system, tort-based liability litigation is replaced by a system which provides basic compensation to wildfire victims, irrespective of the cause and associated fault. However, reform of insurance regulation and zoning are also required.

North Atlantic and the Barents Sea variability contribute to the 2023 extreme fire season in Canada

In the late spring to summer season of 2023, Canada witnessed unprecedented wildfires, with an extensive burning area and smoke spreading as far as the East Coast of the United States and Europe. Here, using multisource data analysis and climate model simulations, we show that an abnormally warm North Atlantic, as well as an abnormally low Barents Sea ice concentration (SIC), are likely key climate drivers of this Canadian fire season, contributing to ~80% of the fire weather anomaly over Canada from June to August 2023. Specifically, the warm North Atlantic forms an anomalous regional zonal cell with ascending air over the Atlantic and descending air encircling Canada, creating hot and dry local conditions. Meanwhile, reduced Barents SIC leads to a high-pressure center and reinforces the dry northern winds in Canada through Rossby wave dynamics. These exacerbated dry and hot conditions create a favorable environment for the ignition and spread of fires, thus contributing to the prolonged and extreme fire season in Canada. These teleconnections can extend to decadal scales and have important implications for understanding and predicting decadal fire activity in Canada and the surrounding regions.

Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and health

Tropical peatland fires generate substantial quantities of airborne fine particulate matter (PM2.5) and in Indonesia are intensified during El Niño-related drought leading to severe air quality impacts affecting local and distant populations. Limited in-situ data often necessitates reliance on air quality models, like that of the Copernicus Atmosphere Monitoring Service, whose accuracy in extreme conditions is not fully understood. Here we demonstrate how a network of low-cost sensors around Palangka Raya, Central Kalimantan during the 2019 fire season, quantified extreme air quality and city-scale variability. The data indicates relatively strong model performance. Health impacts are substantial with estimates of over 1200 excess deaths in the Palangka Raya region, over 3200 across Central Kalimantan and more than 87,000 nationwide in 2019 due to fire-induced PM2.5 exposure. These findings highlight the need for urgent action to mitigate extreme fire events, including reducing fire use and landscape remediation to prevent peat fire ignition.

Future climate-driven escalation of Southeastern Siberia wildfires revealed by deep learning

The Southeastern Siberia (SES) region has recently experienced increasingly extensive wildfires in spring, which have threatened its large carbon sequestration capacity from vast forests and peatlands. However, the underlying mechanisms propelling the increased fires and their potential responses to future climate change remain unclear. Here, by using reanalysis data and climate model output together with a deep learning model, we explore the relationship between positive-phase North Atlantic Tripole (NAT) sea-surface temperature anomalies and SES wildfire increases and project the future trend in SES wildfire intensities under climate change. We found that the positive-phase April NAT enhances the Siberian anticyclone, causing increased temperatures and snowmelt via strengthened transport of warm-air advection into the SES region. The latter process heightens the exposure of local high-density peatlands to favorable conditions for fire ignition and leads to more intensive wildfire incidents. We further demonstrate that the projected NAT variations can drive interdecadal changes in future April SES wildfires. With future phase shifting of NAT modes under global warming, the regionally averaged burned area in SES could be increased by 47–62% under different warming scenarios from 1982–2014 to 2015–2100. Our findings reveal the climate-driven escalation of future wildfires in SES in the context of global warming and call for active and urgent fire management strategies to mitigate the fire risk.

Assessing the Cascading Post-Earthquake Fire-Risk Scenario in Urban Centres

The frequency of urban fires has grown in recent years everywhere, especially in historic districts, including in Portugal, due to the existence of sensitive igniting materials, the proximity of buildings, the complex urban layout, and the presence of many people. The current study proposes a technique, applied in the Baixa Pombalina (downtown) area in Lisbon, to undertake an appropriate evaluation of the post-earthquake fire cascading effect, which may cause major damage. The earthquake vulnerability and damage scenario were carried out using the Risk-UE method. An empirical fire ignition model was then applied to determine the quantity and location of fire ignitions for different return periods. Furthermore, the simple fire spread Hamada’s model was applied to both the equally spaced grid buildings, as in the original Hamada procedure, and the current study area layout for different time thresholds. Finally, the risk assessment for both models was carried out, allowing for the estimation of earthquake and fire losses, respectively. The results demonstrated that the models are comparable, showing that the Hamada model might be a useful tool for large-scale evaluations aimed at disaster-risk reduction and management since it gives useful information for managing and reducing natural and anthropogenic hazards.

Investigation into the mechanism of ignition of magnesium alloy plates by high-temperature molten droplet

The ignition and spread of magnesium alloy fires are mainly attributed to the ignition of high-temperature molten metal droplets, but the underlying ignition mechanism remains unclear. This study addresses this knowledge gap by employing metallic aluminum and copper particles heated to temperatures over 1200 °C. Systematically, these heated particles were released at a fixed rate onto a magnesium alloy plate located inside a controlled heating furnace that maintained a constant temperature of 500 °C. Experimental results show that whether there are irregular pores and cracks in the resulting molten product can be used as a criterion for judging whether the magnesium alloy sample ignites. Furthermore, it is worth noting that molten copper droplets of the same size exhibit a higher heat-carrying capacity than their aluminum counterparts when both are heated to the same temperature. In addition, this study expanded the research scope through numerical simulation and analysis, using the PATO (Porous-Material Analysis Toolbox) solver to clarify the transient heat conduction process between the high-temperature droplet and the magnesium alloy plate. Simulations show that heat transfer upon droplet impact is primarily longitudinal, directed toward the base of the material. This results in a significantly higher temperature in the center of the affected magnesium alloy plate than at its periphery. In summary, this study helps to improve the understanding of the dangers of high-temperature molten droplets, and it is of great significance to investigate fire accidents caused by high-temperature molten droplets.

A Study to Assess Knowledge Regarding Fire Safety and Their Practices among Third Year B.Sc. Nursing Students with a view to Develop on Hand Training Module

Background: Fire safety is the set of practices intended to prevent the destruction caused by Fire. Fire safety is the set of practices intended to reduce destruction caused by fire. Fire safety measures include those that are intended to prevent the ignition of an uncontrolled fire and those that are used to limit the spread and impact of a fire.[4] Fire related accidents have, on average, killed 35 people every day over the five years between 2016 and 2020, according to a report by the National Crime Records Bureau (NCRB). Aims and Objectives: To Assess the knowledge regarding Fire Safety and their practices among the students of 3rd year B.Sc. Nursing, Ambaji Nursing College, Ganeshpura, and to find out Association between selected demographic variable and to develop on hand training module. Materials and Method: The study was conducted among 60 students of Ambaji Nursing College, Ganeshpura and using simple random sampling technique. Data were obtained using structured knowledge questionnaire to assess the knowledge regarding Fire safety and their practices. Descriptive and Inferential statistics were use to analyze the Demographic data and used structured questionnaire. Karl person formula is used to determine Correlation whereas the Association is determined by using Chi -Square formula. Results and Conclusion: The study revealed that majority of students level of knowledge are 36.70% poor knowledge, 61.70% students are average knowledge and 1.70% students are good knowledge regarding fire safety and their practices. There exist positive moderate correlation (r = 0.75) between knowledge and their practices. Study also revealed there is no significant Association between the knowledge and their demographic variables such as Age, Gender, Annual household income, Religion and attending any training of fire safety practices at p ≤ 0.05 level.

Trees have similar growth responses to first-entry fires and reburns following long-term fire exclusion

Managing fire ignitions for resource benefit decreases fuel loads and reduces the risk of high-severity fire in fire-suppressed dry conifer forests. However, the reintroduction of low-severity wildfire can injure trees, which may decrease their growth after fire. Post-fire growth responses could change from first-entry fires to reburns, as first-entry fires reduce fuel loads and the vulnerability among trees to fire effects, which may result in trees sustaining less damage during reburns. To determine whether trees had growth responses that varied from first-entry fires to reburns, we cored 87 ponderosa pine trees in the Gila Wilderness, New Mexico, USA that experienced 3–5 fires between 1950 and 2012 following long-term fire-exclusion and 67 unburned control trees from the Gila and Apache-Sitgreaves National Forests. We assessed tree growth response to fire by comparing tree-ring growth among burned and unburned trees from two years before to two years after fires. We compared growth between burned and unburned trees using a bootstrapping procedure to calculate annual median tree-ring width index values with 95 % confidence intervals. We compared post-fire growth after first-entry fires and reburns following long-term fire-exclusion. Burned trees had similar growth responses following first-entry fires and reburns, with lower growth during the fire year through two years post-fire compared to unburned controls. Burned tree growth returned to expected rates following these immediate post-fire growth reductions. Interestingly, trees had lower growth during the year before and the year of reburns compared to the first-entry fire, reflecting greater aridity before reburns. Greater aridity may have contributed to larger-than-expected growth reductions following reburns, which could explain similar growth responses to first-entry fires and reburns. Our results indicate that trees had consistent short-term growth responses to low-severity fires following long-term fire-exclusion. As trees retained vigor after multiple fires, managing fires for resource benefit is an effective approach to reduce the likelihood of high-severity fire without long-term negative effects on tree growth.

Modernizing the US National Fire Danger Rating System (version 4): Simplified fuel models and improved live and dead fuel moisture calculations

The US National Fire Danger Rating System (USNFDRS) supports wildfire management decisions nationwide, but it has not been updated since 1988. Here we implement new fuel moisture models, and we simplify the fuel models while maintaining the overall USNFDRS structure. Modeled and measured live fuel moisture content values were highly correlated (r2=0.629 with defaults and r2=0.693 when species and location optimized). We also consolidated fuel models to five fuel types that eliminated significant index cross-correlation. Index seasonality compared between old (V2) and new USNFDRS models (v4) across six US National Forests was very similar (ρ= 0.97). V4 was as good or better than V2 at predicting fire days in 92% of the cases tested and V4 effectively predicted wildfire days and large fire ignition days (AUCs 0.647 to 0.915). USNFDRS V4 can adequately depict spatial and temporal wildland fire potential and it can be adapted for worldwide use.

Comparing Ignition of Fuel Beds to Firebrand Showers to Ignition of Fuel Beds by Non-Reacting Heaters

ABSTRACT The combustion of various fuels results in the release of firebrands during wildland-urban interface (WUI) fires. Firebrands represent a hazard, since the release of firebrands may lead to multiple ignitions at locations distant from the original combustion source. A newly developed experimental protocol using a non-reacting heater was used to simulate a firebrand. A direct comparison of this simplified non-reacting heater setup was undertaken to realistic fuel bed ignition to actual firebrand showers. Firebrand showers were generated using a custom experimental setup developed for this investigation. The novelty of this research is a detailed comparison for the first time to fuel bed ignition from non-reacting heaters to actual firebrand showers, for the same fuel bed type. The focus here is on smoldering ignition (SI) of the fuel beds, as this is seen as a complex and least understood aspect of firebrand ignition of actual WUI fires. Results indicate that the overall phenomenology of the ignition process is different between a non-reacting cartridge heater and a shower of firebrands. Complicated smoldering ignition phenomena of fuel beds by firebrand showers cannot be simulated by a simple non-reacting heater.

Scintilla: Simulating Combustible Vegetation for Wildfires

Wildfires are a complex physical phenomenon that involves the combustion of a variety of flammable materials ranging from fallen leaves and dried twigs to decomposing organic material and living flora. All these materials can potentially act as fuel with different properties that determine the progress and severity of a wildfire. In this paper, we propose a novel approach for simulating the dynamic interaction between the varying components of a wildfire, including processes of convection, combustion and heat transfer between vegetation, soil and atmosphere. We propose a novel representation of vegetation that includes detailed branch geometry, fuel moisture, and distribution of grass, fine fuel, and duff. Furthermore, we model the ignition, generation, and transport of fire by firebrands and embers. This allows simulating and rendering virtual 3D wildfires that realistically capture key aspects of the process, such as progressions from ground to crown fires, the impact of embers carried by wind, and the effects of fire barriers and other human intervention methods. We evaluate our approach through numerous experiments and based on comparisons to real-world wildfire data.

Enhancing smoke management in underground parking areas using jet fan systems with a focus on dead-end areas

This study delves into the utilization of jet fans in underground parking structures for smoke management during fires, with a specific focus on enhancing smoke control near critical areas adjacent to dead-end sections through innovative jet fan designs. Through the analysis of airflow patterns and computational fluid dynamic simulations, the research aims to effectively contain smoke and prevent its dispersion to unaffected zones. Findings underscore the significance of parking layout designs in ventilation strategies and soot dispersion rates. Altering the downward orientation of the jet fan outlet results in a notable portion of smoke being confined within the parking facility. Additionally, widening the jet fan outlet, as proposed in the design, can enhance smoke evacuation in all directions. Two hazard detection scenarios were executed within the parking structure following the British standard (BS), with one scenario simulated as a fire ignition source. The chosen scenario considers all escape routes and evacuation procedures within the underground parking area based on architectural specifications. By employing OpenFOAM software with the buoyantBoussinesqPimpleFOAM solver, the study assesses the efficacy of this approach, achieving a reduction in airflow irregularities of over 30%. It also provides valuable insights for designers to refine their comprehension of jet fan design, recommending tailored designs for specific zones. This research offers practical guidance for designers to optimize jet fan configurations for effective smoke control in underground parking facilities.

Spot ignition of a wildland fire and its transition to propagation

Spot ignition of a wildland fire and its transition to propagation

PostBP: A Python library to analyze outputs from wildfire growth models

Wildfire is an important natural disturbance agent in Canadian forests, but it has also caused significant economic damage nationwide. Spatial fire growth models have emerged as important tools for representing wildfire dynamics across diverse landscapes, enabling the mapping of key wildfire hazard metrics such as location-specific burn probabilities or likelihoods of fire ignition. While these summary metrics have gained popularity, they often fall short in capturing the directional spread of wildfires and their potential spread distances. The metrics depicting the directional spread of wildfire can be derived from raw outputs generated with fire growth models, such as the perimeters and ignition locations of individual fires, but extracting this information requires complex data processing. To address this data gap, we present PostBP, an open-source Python package designed for post-processing the raw outputs of fire growth models — the ignition locations and perimeters of individual fires simulated over multiple stochastic iterations — into a matrix of fire spread likelihoods between all pairs of forest patches in a landscape. The PostBP also generates several other summary outputs, such as the source-sink ratio and the fire spread rose diagram. We provide an overview of PostBP's capabilities and demonstrate its practical application to a forested landscape.•Wildfire growth models generate large amounts of outputs, which are hard to summarize for practical decision-making.•The PostBP package calculates the summary metrics characterizing the directional spread of wildfires.•The fire risk summaries generated with PostBP can support the assessments of wildfire risk and mitigation measures.

Future fire events are likely to be worse than climate projections indicate – these are some of the reasons why

Background Climate projections signal longer fire seasons and an increase in the number of dangerous fire weather days for much of the world including Australia. Aims Here we argue that heatwaves, dynamic fire–atmosphere interactions and increased fuel availability caused by drought will amplify potential fire behaviour well beyond projections based on calculations of afternoon forest fire danger derived from climate models. Methods We review meteorological dynamics contributing to enhanced fire behaviour during heatwaves, drawing on examples of dynamical processes driving fire behaviour during the Australian Black Summer bushfires of 2019–20. Results Key dynamical processes identified include: nocturnal low-level jets, deep, unstable planetary boundary layers and fire–atmosphere coupling. Conclusions The future scenario we contend is long windows of multi-day fire events where overnight suppression is less effective and fire perimeters will expand continuously and aggressively over multiple days and nights. Implications Greater overnight fire activity and multi-day events present strategic and tactical challenges for fire management agencies including having to expand resourcing for overnight work, manage personnel fatigue and revise training to identify conditions conducive to unusually active fire behaviour overnight. Effective messaging will be critical to minimise accidental fire ignition during heatwaves and to alert the community to the changing fire environment

Lightning-induced fire regime in Portugal based on satellite-derived and in situ data

Fire databases typically contain information regarding the location, timing, and duration of fire occurrences, as well as the cause (natural or human-induced). These databases allow for the analysis and understanding of the circumstances surrounding the ignition and propagation of wildfires, being highly relevant when addressing fire suppression and management plans, or for improvement of prevention policies. In Portugal, a large number of fires in the official database have unknown causes, which limits the understanding about the relevance of each fire cause, in particular the role of lightning on the ignition of fires over the country. The objective of this paper is twofold: first, we investigated the spatial-temporal variability of lightning-induced fires from 2003 to 2020. Then, we evaluate the feasibility of using remote sensing data as a surrogate for identifying fire causes, through validation with the fire database. Our results revealed that lightning-ignited fires represent an even smaller fraction of all fire events than mentioned in the latest official report about fire causes in the country, accounting for only 1 % of the fire occurrences and 4.6 % of the total burned area in the 18-year period under analysis. The months of June to September comprise 91 % of all lightning fires, which occur more frequently in the northern, remote regions of the country and at relatively high altitudes. Moreover, lightning ignitions originate fires larger than the global average and contributed significantly to the total area burned during the extreme 2003 and 2017 fire seasons. Its importance in these extreme years suggests that lightning can trigger large fires when in conjunction with compound events such as droughts and heatwaves. When compared with in-situ databases, the application of remote sensing data reproduced the seasonality of lightning-ignited fires, but failed to account for the contribution of smaller fires, which represent the majority of occurrences in the Portuguese fire database. Finally, we discuss the implications of our findings for the improved assessment of fire risks, causes, and impacts in Portugal.

Towards early forest fire detection and prevention using AI-powered drones and the IoT

Wildfires are a significant natural hazard, resulting in financial losses, human deaths, and environmental damage. Due to the rising severity and frequency of wildfires, wildfire management and detection have recently received increased attention worldwide. Monitoring potential risk areas and early fire detection are critical factors for shortening the reaction time and reducing the potential damage. Conventional wildfire detection techniques like satellite imaging and remote camera-based sensing need more latency and low reliability. To tackle these limitations, this paper proposes a novel airborne UAV-based IoT (UIoT) system for wildfire sensing, detection, and extinguishing. It presents the design of low-cost and low-maintenance fire-detecting IoT nodes for large-scale deployment. It also proposes, investigates, and reports on several connectivity architectures using the LoRaWAN protocol for UIoT systems. We geolocate forest trees in a terrain-mapping exercise for precise fire localization. We then deploy an autonomous drone with a visual camera that utilizes our novel classification network to detect the presence of fire followed by fire detection and particle filter-based tracking to center fire at the center of the frame. We use a cloud back-end server for monitoring, analysis, and reporting. Our results show that our low-cost and long-range IoT nodes accurately detect fire within 1-5 min after fire ignition. Our fire classification network achieved an accuracy of 99.46% and a mean average precision of 99.64%. Numerical results suggest that the proposed UAV-IoT-based fire classification offers a fast and reliable wildfire recognition and extinguishing solution while minimizing power consumption and increasing the battery lifespan.

3D Location of Indoor Fire Ignition with a Multilevel Constraint Based on Monocular Vision

3D Location of Indoor Fire Ignition with a Multilevel Constraint Based on Monocular Vision