Search Results (434)

Wildland fires are a common and destructive natural disaster in Alaska. Recent active fires in Alaska were assessed and analysed for their associated synoptic-scale climatic conditions in this study. Hotspot (HS) data from satellite observations over the past 20 years since 2004 (total number of HS = 300,988) were used to identify active fire-periods, and the occurrence of Rossby wave breaking (RWB) was examined using various weather maps. Analysis results show that there are 13 active fire-periods of which 7 active fire-periods are related to RWB. The total number of HSs during the seven RWB-related fire-periods was 164,422, indicating that about half (54.6%) of the recent fires in Alaska occurred under fire weather conditions related to RWB. During the RWB-related fire-periods, two hotspot peaks with different wind directions occurred. At the first hotspot peak, southwesterly wind blew from high-pressure systems in the Gulf of Alaska. In the second hotspot peak, the Beaufort Sea High (BSH) supplied strong easterly wind into Interior Alaska. It was suggested that changes in wind direction during active fire-period and continuously blowing winds from BSH may affect fire propagation. It is hoped that this study will stimulate further research into active fires related to RWBs in Alaska. Full article

In 1961, Los Angeles experienced the disastrous Bel Air fire, which swept through an affluent neighborhood situated in a hilly, WUI (wildland–urban interface) location. In January 2025, the city was devastated again by a nearly-simultaneous series of wildfires, the most severe of which took place close to the 1961 fire location. Disastrous WUI fires are, unfortunately, an anticipatable occurrence in many U.S. cities. A number of issues identified earlier remained the same. Some were largely solved, while other new ones have emerged. The paper examines the Palisades Fire of January, 2025 in this context. In the intervening decades, the population of the city grew substantially. But firefighting resources did not keep pace. Very likely, the single-most-important factor in causing the 2025 disasters is that the Los Angeles Fire Department operational vehicle count shrank to 1/5 of what it was in 1961 (per capita). This is likely why critical delays were experienced in the initial attack on the Palisades Fire, leading to a runaway conflagration. Two other crucial issues were the management of vegetation and the adequacy of water supplies. On both these issues, the Palisades Fire revealed serious problems. A problem which arose after 1961 involves the unintended consequences of environmental legislation. Communities will continue to be devastated by wildfires unless adequate vegetation management is accomplished. Yet, environmental regulations are focused on maintaining the status quo, often making vegetation management difficult or ineffective. House survival during a wildfire is strongly affected by whether good vegetation management practices and good building practices (“ignition-resistant” construction features) have been implemented. The latter have not been mandatory for housing built prior to 2008, and the vast majority of houses in the area predated such building code requirements. California has also suffered from a highly counterproductive stance on insurance regulation. This has resulted in some residents not having property insurance, due to the inhospitable operating conditions for insurance firms in the state. Because of the historical precedent, the details in this paper focus on the Palisades Fire; however, many of the lessons learned apply to managing fires in all WUI areas. Policy recommendations are offered, which could help to reduce the potential for future conflagrations. Full article

In the United States, ecosystems regularly experience wildfires and as fire seasons lengthen, fires are becoming a more important disturbance. While all types of disturbance have impacts on the carbon cycle, fires result in immediate emissions into the atmosphere. To assist managers in assessing wildland fire impacts, particularly on federally managed land, we developed estimates of area burned and related emissions for a 21-year period. These estimates are based on wildland fires defined by the interagency Monitoring Trends in Burn Severity database; emissions are simulated through the Wildland Fire Emissions Inventory System; and the classification of public land is performed according to the US Geological Survey’s Protected Areas Database of the United States. Wildland fires on federal land contributed 62 percent of all annual CO₂ emissions from wildfires in the United States between 2001 and 2021. During this period, emissions from the forest fire subset of wildland fires ranged from 328 Tg CO₂ in 2004 to 37 Tg CO₂ in 2001. While forest fires averaged 38 percent of burned area, they represent the majority—59 to 89 percent of annual emissions—relative to fires in all ecosystems, including non-forest. Wildland fire emissions on land belonging to the federal government accounted for 44 to 77 percent of total annual fire emissions for the entire United States. Land managed by three federal agencies—the Forest Service, the Bureau of Land Management, and the Fish and Wildlife Service—accounted for 93 percent of fire emissions from federal land over the course of the study period, but year-to-year contributions varied. Full article

Despite recent advances in deep learning for fire detection, much of the current research prioritizes model-centric metrics over dataset fidelity, particularly from a fire safety engineering perspective. Commonly used datasets are often dominated by fully developed flames, mislabel smoke-only frames as non-fire, or lack intra-video diversity due to redundant frames from limited sources. Some works treat smoke detection alone as early-stage detection, even though many fires (e.g., electrical or chemical) begin with visible flames and no smoke. Additionally, attempts to improve model applicability through mixed-context datasets—combining indoor, outdoor, and wildland scenes—often overlook the unique false alarm sources and detection challenges specific to each environment. To address these limitations, we curated a new video dataset comprising 1108 annotated fire and non-fire clips captured via indoor surveillance cameras. Unlike existing datasets, ours emphasizes early-stage fire dynamics (pre-flashover) and includes varied fire sources (e.g., sofa, cupboard, and attic fires), realistic false alarm triggers (e.g., flame-colored objects, artificial lighting), and a wide range of spatial layouts and illumination conditions. This collection enables robust training and benchmarking for early indoor fire detection. Using this dataset, we developed a spatiotemporal fire detection model based on the mixed convolutions ResNets (MC3_18) architecture, augmented with Convolutional Block Attention Modules (CBAM). The proposed model achieved 86.11% accuracy, 88.76% precision, and 84.04% recall, along with low false positive (11.63%) and false negative (15.96%) rates. Compared to its CBAM-free baseline, the model exhibits notable improvements in F1-score and interpretability, as confirmed by Grad-CAM++ visualizations highlighting attention to semantically meaningful fire features. These results demonstrate that effective early fire detection is inseparable from high-quality, context-specific datasets. Our work introduces a scalable, safety-driven approach that advances the development of reliable, interpretable, and deployment-ready fire detection systems for residential environments. Full article

Ensuring proper sizing and fit for U.S. female firefighters’ personal protective clothing and equipment (PPE) is a crucial challenge for researchers and manufacturers. The National Fire Protection Association (NFPA) establishes design and performance standards in the U.S., with NFPA 1977 specifying sizing guidelines for wildland firefighting gear. However, the absence of an anthropometric database representing female firefighters limits the effectiveness of these standards. This research evaluates the effectiveness of NFPA 1977 sizing system by investigating whether correlated body measurements maintain internal consistency and provide data-driven recommendations for improvement. Anthropometric data from 187 U.S. female firefighters were analyzed to assess the 2016 and 2022 NFPA 1977 upper and lower torso sizing systems. Correlation analysis was performed between body measurements and corresponding sizes. Contingency tables presented proportion of participants accommodated. Results indicated significant correlations between chest and wrist measurements and sizes in the upper torso, though these were the only available measurements. In the lower torso, hip size strongly correlated with thigh and knee sizes. However, the system inadequately accommodates female firefighters with larger waist and hip measurements. Furthermore, rise sizes demonstrated inconsistent, weak relationships with hip circumference. Overall, the NFPA 1977 sizing requires revision to better serve U.S. female firefighters. Full article

With wildfires becoming more frequent and severe in fire-prone regions affected by warmer and drier climate conditions, reducing hazardous fuels is increasingly recognized as a preventative strategy for promoting sustainability and safeguarding valued resources. Prescribed fire is one of the most cost-effective methods for reducing hazardous fuels and hence wildfire severity, yet empirical research on its effectiveness at minimizing damage to highly valued resources and assets (HVRAs) remains limited. The overarching objective of this study was to evaluate wildfire severity under differing weather conditions across various HVRAs characterized by diverse land uses, vegetation types, and treatment histories. The findings from this study reveal that wildfire severity was generally lower in areas treated with prescribed fire, although the significance of this effect varied among HVRAs and diminished as post-treatment duration increased. The wildland–urban interface experienced the greatest initial reduction in wildfire severity following prescribed fire, but burn severity increased more rapidly over time relative to other HVRAs. Elevated drought conditions had a significant effect, increasing wildfire severity across all HVRAs. The implications of this study underscore the role of prescribed fire in promoting sustainable land management by reducing wildfire severity and safeguarding both natural and built environments, particularly in the expanding wildland–urban interface. Full article

Urbanization, habitat fragmentation, and intensifying urban heat island (UHI) effects accelerate biodiversity loss and diminish ecological resilience in cities, particularly in climate-vulnerable regions. To address these challenges, we developed TreeGrid, a functionality-based spatial tree planning tool designed specifically for urban settings in the Northern Plains of India. The tool integrates species trait datasets, ecological scoring metrics, and spatial simulations to optimize tree placement for enhanced ecosystem service delivery, biodiversity support, and urban cooling. Developed within an R Shiny framework, TreeGrid dynamically computes biodiversity indices, faunal diversity potential, canopy shading, carbon sequestration, and habitat connectivity while simulating localized reductions in land surface temperature (LST). Additionally, we trained a deep neural network (DNN) model using tool-generated data to predict bird habitat suitability across diverse urban contexts. The tool’s spatial optimization capabilities are also applicable to post-fire restoration planning in wildland–urban interfaces by guiding the selection of appropriate endemic species for revegetation. This integrated framework supports the development of scalable applications in other climate-impacted regions, highlighting the utility of participatory planning, predictive modeling, and ecosystem service assessments in designing biodiversity-inclusive and thermally resilient urban landscapes. Full article

Increasing wildfire activities across the Great Plains has raised concerns about the effectiveness and safety of prescribed fire as a land management tool. This study analyzes wildfire records from 1992 to 2020 to assess spatiotemporal patterns in wildfire risk and evaluate the role of prescribed fires through the combined analysis of wildfire and prescribed fire data. Results show a threefold increase in both wildfire frequency and area burned, with fire size increasing from east to west and frequency rising from north to south. Wildfire seasons are gradually occurring earlier due to climate change. Negative correlation between prescribed fires in spring and wildfires in summer indicated the effectiveness of prescribed fire in mitigating wildfire risk. Drought severity accounted for 51% of the interannual variability in area burned, while grass curing accounted for 60% of monthly variability of wildfires in grasslands. The ratio of wildfire area burned to total area burned (dominated by prescribed fires) declined from over 20% in early March to below 1% by early April. The results will lay a foundation for the development of a localized fire risk assessment tool that integrates various long-term, mid-term, and short-term risk factors, and support more effective fire management in this region. Full article

Wildfires pose significant threats to ecosystems, human lives, and property worldwide. Understanding the behavior of fire spread on sloped terrain is essential for developing effective firefighting strategies and improving fire prediction models. Previous research has successfully demonstrated the accuracy of numerical tools in comparison to laboratory experiments. This study focuses on the influence of terrain slope and wind speed on wildland fire behavior using Computational Fluid Dynamics (CFD) simulations. In the first phase, the numerical model was validated for a 5 m high single Douglas Fir tree under various mesh sizes, yielding heat release and mass loss rates in close agreement with experimental data. The second phase extends the model to simulate a plantation of 66 Douglas Fir trees under varying slopes and wind conditions. The results indicate that a downward slope of 30° reduces the peak heat release rate, while an upward slope of 30° increases it, with wind speed amplifying these effects. Based on these data, a new reduced-order model is proposed to quantify the influence of slope angle on the heat release rate (HRR) in wildland fires. These findings are critical for enhancing predictive fire models and mitigating wildfire risks in complex terrains. Full article

Wildfires in central-south Chile, consistent with trends observed in other Mediterranean regions, are expected to become more frequent and severe, threatening ecosystems and impacting millions of people. This study aims to enhance wildfire resilience in the central-south regions of Chile through the provision of robust information on current wildfire management practices and comparison with successful alternatives implemented in other fire-prone Mediterranean regions. With this aim, we consulted 55 local stakeholders involved in wildfire management, and alongside a comparative analysis of wildfire statistics and resource allocation in selected Mediterranean regions, we critically assessed different strategies to improve wildfire prevention and management in central-south Chile. The comparative analysis indicated notable economic under-investment for wildfire prevention in Chile. Compared to other Mediterranean countries, Chile is clearly below in terms of investment in forest fire prevention, both in global (public investment) and specific terms ($ ha⁻¹, GDP per capita). The experts consulted included fuel management, governance and community participation, territorial management, landscape planning, socioeconomic evaluation, and education and awareness as key aspects for wildfire prevention. The results of the questionnaire indicated that there was a broad consensus regarding the importance of managing biomass to reduce fuel loads and vegetation continuity, thereby enhancing landscape resilience. Landscape planning and territorial management were also emphasized as critical tools to balance ecological needs with those of local communities, mitigating wildfire risks. Fire-Smart management emerged as a nature-based solution and a promising integrated approach, combining fuel treatments with modeling, simulation, and scenario evaluation based on local and regional environmental data. Additionally, educational and social engagement tools were considered vital for addressing misconceptions and fostering community support. Besides a better integration of rural planning with social demands, this study underscores the urgent need to substantially increase the investment and significance of wildfire prevention measures in central-south Chile, which are key to improving its wildfire resilience. Our work contextualizes the reality of wildfires in central-south Chile and directly contributes to mitigating this growing concern by critically examining successful wildfire resilience strategies from comparable fire-prone regions, complementing ongoing local efforts and offering a practical guide for stakeholders in wildfire management and prevention, with particular relevance to central-south Chile and other regions with similar characteristics. Full article

The wildland–urban interface (WUI) has been a global phenomenon, yet parameter threshold determination remains a persistent challenge in this field. In China, a significant research gap exists in the development of WUI mapping methodology. This study proposes a novel mapping approach that delineates the WUI by integrating both vegetation and building environment perspectives. GaoFen 1 Panchromatic Multi-spectral Sensor (GF1-PMS) imagery was leveraged as the data source. Building location was extracted using object-oriented and hierarchical classification techniques, and the pixel dichotomy method was employed to estimate fractional vegetation coverage (FVC). Building location and FVC were used as input for the WUI mapping. In this methodology, the threshold of FVC was determined by incorporating the remote sensing characteristics of the WUI types, whereas the buffer range of vegetation was refined through sensitivity analysis. The proposed method demonstrated high applicability in Anning City, achieving an overall accuracy of 88.56%. The total WUI area amounted to 49,578.05 ha, accounting for 38.08% of Anning City’s entire area. Spatially, the intermix WUI was predominantly distributed in the Taiping sub-district of Anning City, while the interface WUI was mainly concentrated in the Bajie sub-district of Anning City. MODIS fire spots from 2003 to 2022 were primarily clustered in the Qinglong sub-district, Wenquan sub-district, and Caopu sub-district of Anning City. Our findings indicated a spatial overlap between the WUI and fire-prone areas in Anning City. This study presents an effective methodology for threshold determination and WUI mapping, making up for the scarcity of mapping methodologies in China. Moreover, our approach offers valuable insights for a wise decision in fire risk. Full article

Governance plays a critical role at the intersection of disaster risk management (DRM) and climate change (CC). As CC increases the frequency and intensity of disasters, so DRM policies must consider the potential impacts of CC and integrate climate resilience measures. Over the past decade, extreme wildfires in wildland–urban interface (WUI) areas have left devastating effects for local economies, local development, environmental protection, and the continuity of government operations worldwide, prompting all actors to work in the same direction to face its changing context. This systematic review of the literature aims to analyze the research trends on wildfire risk governance in WUI areas during 2021–2024 and to identify the key risk governance determinants, thereby offering a robust foundation to guide technical discussions and support decision-making processes in local development planning, land use regulation, and DRM. The study is based on the application of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) declaration to allow the identification, selection, analysis, and systematization of 68 articles from the Scopus database through three bibliographic search equations, which were then categorized using the software of text mining and natural language processing NLP software (VantagePoint 15.2) to identify four key pillars that structure extreme wildfire risk governance: political management, development planning, disaster risk management, and resilience management. Within this framework, ten governance determinants are highlighted, encompassing aspects such as regulatory frameworks, institutional coordination, information systems, technical capacities, community engagement, risk perception, financial resources, accountability mechanisms, adaptive planning, and cross-sectoral integration. These findings provide a conceptual basis for strengthening governance approaches in the face of increasing wildfire risk. Full article

In response to the escalating complexity and frequency of wildland fires, this study investigates the feasibility of using wearable devices for real-time monitoring of cardiac, respiratory, physical, and environmental parameters during live wildfire suppression tasks. Data were collected from twelve male firefighters (FFs) from the Italian National Fire Corp during a simulated protocol, including rest, running, and active fire suppression phases. Physiological and physical metrics such as heart rate (HR), heart rate variability (HRV), respiratory frequency (f_R) and physical activity levels were extracted using chest straps. The protocol designed to mimic real-world firefighting scenarios revealed significant cardiovascular and respiratory strain, with HR often exceeding 85% of age-predicted maxima and sustained elevations in high-stress roles. Recovery phases highlighted variability in physiological responses, with reduced HRV indicating heightened autonomic stress. Additionally, physical activity analysis showed task-dependent intensity variations, with debris management roles exhibiting consistently high exertion levels. These findings demonstrate the relevance of wearable technology for real-time monitoring, providing an accurate analysis of key metrics to offer a comprehensive overview of work-rest cycles, informing role-specific training and operational strategies. Full article

Wildfires pose increasing risks to human settlements, particularly in the Wildland–Urban Interface (WUI). This study examines the relationship between land cover (LC) characteristics and housing destruction during the 2023 wildfires in Chile’s Bío-Bío region. Using high-resolution remote sensing data and GIS-based multi-buffer spatial analysis (30 m and 100 m), we assessed LC patterns around affected and unaffected rural houses. Results indicate that the proximity of forest plantations significantly increased housing loss, with a notably higher presence of plantations within 30 m of destroyed houses. In contrast, agricultural and pasture mosaics demonstrated a protective function by reducing fire spread. Shrublands also showed moderate protection, albeit with statistical uncertainty. The findings highlight the critical role of immediate LC in determining wildfire impact, emphasizing the need for integrating LC considerations into wildfire risk management, land-use planning, and policy interventions. Strategies such as creating defensible spaces, enforcing zoning regulations, and promoting fire-resistant landscapes can help mitigate future wildfire damage. This research provides spatially explicit insights that contribute to wildfire risk reduction theory and inform targeted prevention and resilience-building strategies in Chile and other fire-prone regions. Full article

Forest fires have become one of the most destructive natural disasters worldwide, causing catastrophic losses, sometimes with the loss of lives. Therefore, some countries have created legislation to enforce mandatory fuel management within buffer zones in the vicinity of buildings and roads. The purpose of this study is to investigate whether inexpensive off-the-shelf drones equipped with standard RGB cameras could be used to detect the excess of trees and vegetation within those buffer zones. The methodology used in this study was the development and evaluation of a complete system, which uses AI to detect the contours of buildings and the services provided by the CHAMELEON bundles to detect trees and vegetation within buffer zones. The developed AI model is effective at detecting the building contours, with a mAP50 of 0.888. The article analyses the results obtained from two use cases: a road surrounded by dense forest and an isolated building with dense vegetation nearby. The main conclusion of this study is that off-the-shelf drones equipped with standard RGB cameras can be effective at detecting non-compliant vegetation and trees within buffer zones. This can be used to manage biomass within buffer zones, thus helping to reduce the risk of wildfire propagation in wildland–urban interfaces. Full article