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Destructive wildfires pose a serious threat to ecosystems, economic development, and human life and property safety. If wildfires can be extinguished in a relatively short period of time after they occur, the losses caused by wildfires will be greatly reduced. Although deep learning methods have been shown to have powerful feature extraction capabilities, many current models still have poor generalization performance when faced with complex tasks. To this end, in this study, we considered introducing attention modules both inside and outside the nested U-shaped structure and trained a neural network model based on the U2-Net architecture to enable the model to suppress the activation of irrelevant areas. Compared with baseline models such as U-Net, our model has made great progress on the test set, with an F1 score improvement of at least 2.8%. The experimental results indicate that the model we proposed has certain practicality and can provide a significant scientific basis for forest fire management and emergency decision-making. [ABSTRACT FROM AUTHOR]

Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is prone to fire, and rapid population growth has created a substantial WUI. Despite this, there is not sufficient research addressing neighborhood-level evacuation risks. The goal of this research, then, is to search Hays County for neighborhoods that face the highest combined risk of wildfire and potential evacuation difficulty. This research provides a limited use case wherein local decision-makers can quantify the combined risk of wildfire and constrained evacuation at the neighborhood scale by making use of standard spatial analysis techniques and publicly available datasets. The results show an alarming trend of low-egress neighborhoods in fire-prone areas within Hays County which carry the risk of a very difficult evacuation in cases when wildfire warning time is short. By using publicly available datasets and standard techniques, this research provides methods for local decision-makers across the state to identify these at-risk neighborhoods within their own jurisdictions which may aid in emergency planning and mitigation. [ABSTRACT FROM AUTHOR]

In 2019, the Chinese government put forward the concept of social co-governance in the field of emergency management. This paper discusses whether the adjustment in the governance concept promotes public participation in emergency management practices and what the mechanisms are to achieve successful public participation in a wildfire emergency. Taking the Beibei wildfire in Chongqing in 2022 as a study case, this paper establishes the public participation mechanisms for wildfire rescue and management with a qualitative case study method. The result shows that adjustments to emergency management concepts and the pressure of wildfire governance make local governments and commanders seek help from the public; key persons and informal networks play an important role in public participation in a wildfire emergency; and constructing social memory in social networks, whether government-led or public-organized, is an important way to enhance public participation in wildfire governance. Our findings, grounded in the reality of the growing complexity of wildfires, provide useful lessons for future wildfire governance in other provinces in China, as well as valuable references for other countries or regions. [ABSTRACT FROM AUTHOR]

Weather conditions that can enhance wildfire potential are a problem faced by many countries around the world. Wildfires can have major economic impacts as well as prolonged effects on populations and ecosystems. Distributing information on fire hazards to the public and first responders in real time is crucial for fire risk management and risk reduction. Although most fires today are caused by people, weather conditions determine if and how fast the fire spreads. In particular, research has shown that atmospheric vapor pressure deficit (VPD) is a key parameter predicting the dryness of vegetation and the available fuel for fires. VPD is determined from the environmental air temperature and relative humidity, both of which are readily obtained from smartphones carried by the public. In this study we use smartphone data from the company Opensignal, collected over almost 4 years and from more than 40 000 users per day, to estimate VPD values. We have found that smartphone data can provide useful information about fire risk and danger. Here we present two case studies from wildfires in Israel and Portugal in which VPD is calculated using calibrated temperature and relative humidity measurements from smartphones. Given the rapid growth in the number of smartphones around the globe, we propose applying smartphone data for meteorological research and fire weather applications. Possible users of these results could be wildfire researchers; public policy specialists in wildfire, climate, and disaster management; engineers working with big data; low-income countries; and citizen science advocates. [ABSTRACT FROM AUTHOR]

In the context of bushfires (and other emergencies), state agencies should avoid developing policy and/or advice that locks people into rigid binary choices. In Victoria, Australia post‐fire inquiries have found the bushfire safety advice often referred to as 'Stay (and defend your property) or Go (early before the fire arrives)' to be contradictory and competing in its logic. However, this advice continues to provide a basis for positive community safety outcomes. It can still be used effectively by policy makers and practitioners within emergency management agencies to inform and educate a highly urbanised society that has become experientially detached from bushfire. With the introduction of the Australian Fire Danger Ratings System and climate challenges ahead, it appears that logics at the core of 'Stay or Go' will continue to offer communities located alongside complex bushfire risk in urban, regional, and rural areas a basis for appropriate safety decisions using the best available information. Points for practitioners: Provides guidelines for ways in which 'Stay or Go' advice can continue to be used by emergency management policy makers and practitioners as a basis for positive community safety outcomes from bushfire risk.Challenges suggestions from significant bushfire inquiries that the logics at the core of 'Stay or Go' contradict each other. Staying and defending a home or leaving early offer a basis for surviving bushfire depending on individual circumstances—practitioners should ensure that this is a key message of bushfire education campaigns.Provides pathways for practitioners and the community to work together and co‐create collaborative bushfire plans whereby preparing for bushfire risk is a shared responsibility. [ABSTRACT FROM AUTHOR]

The global increase in wildfires due to climate change highlights the need for accurate wildfire mapping. This study performs a proof of concept on the usefulness of SuperDove imagery for wildfire mapping. To address this topic, we present an automatic methodology that combines the use of various vegetation indices with clustering algorithms (bisecting k-means and k-means) to analyze images before and after fires, with the aim of improving the precision of the burned area and severity assessments. The results demonstrate the potential of using this PlanetScope sensor, showing that the methodology effectively delineates burned areas and classifies them by severity level, in comparison with data from the Copernicus Emergency Management Service (CEMS). Thus, the potential of the SuperDove satellite sensor constellation for fire monitoring is highlighted, despite its limitations regarding radiometric distortion and the absence of Short-Wave Infrared (SWIR) bands, suggesting that the methodology could contribute to better fire management strategies. [ABSTRACT FROM AUTHOR]

Natural disasters have an economic impact, affecting buildings and infrastructures. These impacts need to be evaluated for easier mitigation analysis. The conventional methods of analyzing the damages caused by natural disasters are expensive and time-consuming. This study presents a new approach that utilizes deep learning to quickly and precisely assess the level of destruction caused by natural disasters, namely earthquakes, floods, wildfires, and hurricanes. The proposed disaster detection analysis model is designed to be both lightweight and efficient, serving as a highly beneficial tool for immediate natural disaster response and optimal resource allocation. The proposed model uses an encoder-decoder architecture. In the encoder, a lightweight backbone incorporates a feature aggregation mechanism that draws inspiration from adjacent contexts to effectively capture the complex patterns linked to damage caused by disasters. At the decoder, we utilize Atrous convolution and self-attention mechanisms to improve the model's ability to accurately define and interpret spatial features. The model is light and simple, performing at 14.8 MB, 3.69 million parameters, and 8.04 gigaflops. We earn 99.1%, 72.3%, 70.9%, and 82.2% for accuracy, F1-score, kappa score, and precision metrics using the xBD dataset. The model achieves consistent performance metrics compared to state-of-the-art models. The proposed model's lightweight nature ensures computation efficiency and facilitates deployment in resource-constrained environments. [ABSTRACT FROM AUTHOR]

Climate change contributes to the increased frequency and intensity of wildfires globally, with significant impacts on society and the environment. However, our understanding of the global distribution of extreme fires remains skewed, primarily influenced by media coverage and regionalised research efforts. This inaugural State of Wildfires report systematically analyses fire activity worldwide, identifying extreme events from the March 2023–February 2024 fire season. We assess the causes, predictability, and attribution of these events to climate change and land use and forecast future risks under different climate scenarios. During the 2023–2024 fire season, 3.9×106 km 2 burned globally, slightly below the average of previous seasons, but fire carbon (C) emissions were 16 % above average, totalling 2.4 Pg C. Global fire C emissions were increased by record emissions in Canadian boreal forests (over 9 times the average) and reduced by low emissions from African savannahs. Notable events included record-breaking fire extent and emissions in Canada, the largest recorded wildfire in the European Union (Greece), drought-driven fires in western Amazonia and northern parts of South America, and deadly fires in Hawaii (100 deaths) and Chile (131 deaths). Over 232 000 people were evacuated in Canada alone, highlighting the severity of human impact. Our analyses revealed that multiple drivers were needed to cause areas of extreme fire activity. In Canada and Greece, a combination of high fire weather and an abundance of dry fuels increased the probability of fires, whereas burned area anomalies were weaker in regions with lower fuel loads and higher direct suppression, particularly in Canada. Fire weather prediction in Canada showed a mild anomalous signal 1 to 2 months in advance, whereas events in Greece and Amazonia had shorter predictability horizons. Attribution analyses indicated that modelled anomalies in burned area were up to 40 %, 18 %, and 50 % higher due to climate change in Canada, Greece, and western Amazonia during the 2023–2024 fire season, respectively. Meanwhile, the probability of extreme fire seasons of these magnitudes has increased significantly due to anthropogenic climate change, with a 2.9–3.6-fold increase in likelihood of high fire weather in Canada and a 20.0–28.5-fold increase in Amazonia. By the end of the century, events of similar magnitude to 2023 in Canada are projected to occur 6.3–10.8 times more frequently under a medium–high emission scenario (SSP370). This report represents our first annual effort to catalogue extreme wildfire events, explain their occurrence, and predict future risks. By consolidating state-of-the-art wildfire science and delivering key insights relevant to policymakers, disaster management services, firefighting agencies, and land managers, we aim to enhance society's resilience to wildfires and promote advances in preparedness, mitigation, and adaptation. New datasets presented in this work are available from 10.5281/zenodo.11400539 (Jones et al., 2024) and 10.5281/zenodo.11420742 (Kelley et al., 2024a). [ABSTRACT FROM AUTHOR]

Objective Setting Participants Design Results Conclusion To explore the experiences of clinician and management stakeholders involved in a rural/metropolitan collaborative mental health disaster response to the 2019–2020 Black Summer bushfires in the Snowy Valleys region of southern New South Wales (NSW), Australia.A mental health and drug health service in the Snowy Valleys region of rural NSW in collaboration with a mental health service from metropolitan Sydney, NSW.Mental health clinicians and managers from a rural health district (n = 6) and a metropolitan health district (n = 8) involved in a collaborative disaster response to the 2019–2020 Black Summer bushfire disaster in the Snowy Valleys region of southern NSW, Australia.An interpretive qualitative study design using semi‐structured individual interviews, with transcripts analysed using Reflexive Thematic Analysis.Thematic findings on participant experiences are presented under three organising constructs of before (stepping up and jumping right in), during (finding a rhythm of working together), and after (profound personal and professional impacts) the mental health disaster response.Participant experiences had shared and distinct components before, during and after the mental health disaster response, culminating in profound personal and professional impacts. Findings highlight positive aspects and challenges for clinicians participating in a rural/metropolitan collaborative mental health disaster response. The findings of this study contribute new knowledge about experiences of mental health clinicians participating in a disaster response after bushfires, from dual perspectives of members of a bushfire‐affected community and those responding from outside a bushfire‐affected community, which may inform ongoing planning of responses to disaster in Australia. [ABSTRACT FROM AUTHOR]

During emergencies, infants and young children are vulnerable. However, Australia lacks emergency planning and guidance specifically addressing the needs of these children and their caregivers. A total of 256 caregivers (predominately mothers) of children aged 0-4 years were surveyed or interviewed about their experiences during and after the summer bushfires in Australia in 2019-20. In addition, 63 emergency responders were surveyed or interviewed regarding their experiences supporting families with young children, including during the 2019-20 bushfires. Analysis of the surveys and interviews revealed parents were under prepared for the bushfires and preparedness was hampered by a lack of tailored guidance for families. Evacuations were often delayed due to lack of planning and were complicated because of the continuing care needs of children. Evacuation centres presented numerous child-safety risks and women who evacuated on their own particularly struggled to care for their children. Parenting children after the bushfires could be challenging and reports of child behaviour difficulties suggest the effects of the emergency on parents had adverse affects on children. Recovery interventions largely overlooked children younger than school age. Caregivers of infants and young children require targeted preparedness, response and recovery support. This research provides evidence to inform planning and to guide development. [ABSTRACT FROM AUTHOR]

Background: Every year, people in Canada are evacuated due to wildland fires to avoid death, injury, and illness from fire and smoke events. Aims: In this paper, we provide an overview of evacuations recorded in the Canadian Wildland Fire Evacuation Database between 1980 and 2021. Methods: Our analysis covers evacuations in Canada from 1980 to 2021. We provide summary statistics including number of evacuations and evacuees, evacuation duration, seasonality, evacuation causes, community types, structure losses, and fatalities. We also investigate temporal and spatial patterns. Key results: Between 1980 and 2021, there were 1393 wildland fire evacuation events with 576,747 people evacuated. During this period, there was an overall increase in frequency of evacuations, number of evacuees, and duration of events. Structure loss occurred during 194 evacuation events, with 4105 homes burned. We estimate wildland fire evacuations cost at least CAD3.7 billion (excluding structural losses), jumping to CAD4.6 billion if we include productivity losses. Indigenous peoples are disproportionately impacted in wildfire evacuations compared to the general Canadian population. Conclusions: Wildland fire evacuations continue to occur across Canada and are increasing. Implications: The findings from this study give us a better understanding of the characteristics of wildland fire evacuations, which can help guide emergency management. This paper summarises data on wildland fire evacuations in Canada between 1980 and 2021. There were 1393 wildland fire evacuation events with 576,747 people evacuated, costing approximately CAD4.6 billion CDN including productivity losses. [ABSTRACT FROM AUTHOR]

The early detection of wildfires is a crucial challenge in environmental monitoring, pivotal for effective disaster management and ecological conservation. Traditional detection methods often fail to detect fires accurately and in a timely manner, resulting in significant adverse consequences. This paper presents FireXplainNet, a Convolutional Neural Network (CNN) base model, designed specifically to address these limitations through enhanced efficiency and precision in wildfire detection. We optimized data input via specialized preprocessing techniques, significantly improving detection accuracy on both the Wildfire Image and FLAME datasets. A distinctive feature of our approach is the integration of Local Interpretable Model-agnostic Explanations (LIME), which facilitates a deeper understanding of and trust in the model's predictive capabilities. Additionally, we have delved into optimizing pretrained models through transfer learning, enriching our analysis and offering insights into the comparative effectiveness of FireXplainNet. The model achieved an accuracy of 87.32% on the FLAME dataset and 98.70% on the Wildfire Image dataset, with inference times of 0.221 and 0.168 milliseconds, respectively. These performance metrics are critical for the application of real-time fire detection systems, underscoring the potential of FireXplainNet in environmental monitoring and disaster management strategies. [ABSTRACT FROM AUTHOR]

Anger is a well-recognised but little understood emotion in postdisaster contexts. For service providers working in recovery environments, it is critical to understand anger to ensure effective supports and interventions are mobilised. This article describes findings from a study conducted four years after the 2009 Victorian Black Saturday bushfires. Thirty-eight community and service-provider participants were interviewed as individuals, dyads, or within focus groups about their own and others' experiences of anger. Postdisaster anger was described as more immediate, intense, and frequent than predisaster, and seen by participants as destructive, productive, and justified. Experiences and understandings differed by gender, and related to aggression, violence, and family violence. Service provision was a key trigger for anger, with leadership styles, community expectations, and community members' level of control over decision making being factors that shaped experience. Based on these findings, five proposed principles for anger-sensitive practice in disaster contexts, along with wider considerations for understanding anger, are provided. IMPLICATIONS This article provides unique understandings of the experience of anger following disaster, which are useful for social workers, community members and leaders, and other service providers. Research findings about anger experiences and outcomes postdisaster are synthesised into proposed principles for practice with disaster-impacted communities (that can potentially build capability prior to disasters). [ABSTRACT FROM AUTHOR]

The climate crisis significantly impacts the health and well-being of older adults, both directly and indirectly. This issue is of growing concern in Canada due to the country's rapidly accelerating warming trend and expanding elderly population. This article serves a threefold purpose: (i) outlining the impacts of the climate crisis on older adults, (ii) providing a descriptive review of existing policies with a specific focus on the Canadian context, and (iii) promoting actionable recommendations. Our review reveals the application of current strategies, including early warning systems, enhanced infrastructure, sustainable urban planning, healthcare access, social support systems, and community engagement, in enhancing resilience and reducing health consequences among older adults. Within the Canadian context, we then emphasize the importance of establishing robust risk metrics and evaluation methods to prepare for and manage the impacts of the climate crisis efficiently. We underscore the value of vulnerability mapping, utilizing geographic information to identify regions where older adults are most at risk. This allows for targeted interventions and resource allocation. We recommend employing a root cause analysis approach to tailor risk response strategies, along with a focus on promoting awareness, readiness, physician training, and fostering collaboration and benchmarking. These suggestions aim to enhance disaster risk management for the well-being and resilience of older adults in the face of the climate crisis. [ABSTRACT FROM AUTHOR]

Climate Change‐induced risk events intensify vulnerability and disproportionately affect regions and racialized immigrant communities. Understanding the multiple dimensions of disaster and risk, especially how these are embedded in a broader social‐political context, and translated into risk management strategies, have now been identified as priority areas under Sendai Framework for Disaster Risk Reduction 2015–2030 and UN Research Roadmap for achieving Sustainable Development Goals (SDGs) 2030. Drawing on a relational intersectional approach, this study explores the meanings of climate change disasters and risk reduction strategies from a racialized immigrant community's (i.e., Bangladeshi‐Canadian) lived experiences in Calgary, Canada. From our relational research, we learned that extreme climate events (such as forest fires/wildfires, heat waves, flash floods, severe colds, hailstorms, etc.) are the most common stressors unevenly impacting the household economy, physical health, and mental and psychological wellbeing of the racialized immigrant community in Calgary. The community's compounded vulnerability to disaster risks is further aggravated due to their intersectional positionality and structural inequality (systematic marginalization) rooted in the lack of explicit anti‐racist policy guidelines in Canada. The community members adapt diverse strategies (mostly reactive) based on their family income, severity and frequency of the exposure to risks, social support system, geographic location (residence), cultural practices, and involvement with community networks. While proposing solutions, they suggested that community‐engaged tailored disaster intervention strategy could play an instrumental role in addressing social vulnerability (determinants) and enhancing adaptive capacity at the local level. Moreover, this study calls for a more holistic account of the differential vulnerability context to better understand the structural root causes and emphasizes that upscaling land‐based practices and knowledge transmission, ensuring deliberate participation of visible minorities, fostering collective action and integrating local community associations into all stages of disaster management should be the priority for the state agencies to support long‐term resilience. [ABSTRACT FROM AUTHOR]

The article provides an overview of various extreme weather events that occurred in 2023. It attributes the global heat to El Niño and global warming, resulting in record-breaking temperatures and droughts in some areas. The year began with extreme heat and cold, accompanied by major flooding in Africa, the Philippines, and New Zealand. The article also mentions the "Zombie Cyclone" that caused heavy rain, high winds, and flooding as it traveled from Indonesia to Madagascar and Mozambique. It further discusses Canada's historic wildfire season, extreme summer heat in North America and Asia, and other notable events such as record-breaking temperatures in Algeria, Morocco, and Albania, scorching temperatures in China, historic flooding in the eastern Mediterranean, deadly monsoon flooding in South Asia, Hurricane Otis in Mexico, and storms in Europe causing flooding and power outages. The article concludes by mentioning the forecasted dissipation of El Niño in 2024, which may result in lower global temperatures. [Extracted from the article]

In disaster management, some crises receive more attention than others. In this article we try to unpack what specific factors make one crisis more interesting than another, by focusing on the experiences of crisis management professionals. In the article, we use a broad set of data including participant observations, interviews and workshops, working with the metaphor of a "festival" to illustrate this phenomenon. We find that the festival metaphor works well to capture distinctive features of this specific kind of crisis, that in turn affects the response. Our results indicate that the festival spirit enables a clarity, where managers feel that they can prioritize the proper response and need not include a range of different perspectives. At the same time, they are aware that positive feelings, in the sense of getting things done, are not to be publicly expressed. We conclude with a discussion on the implications for crisis response and the possibility of working with metaphors. [ABSTRACT FROM AUTHOR]

In 2023, Greece faced its worst wildfire season, with nine major fires causing unprecedented environmental damage of 1470.31 km2. This article uses Copernicus Land Monitoring Service and Sentinel-2 data, employing advanced remote sensing and GIS techniques to analyze spatial dynamics, map burn severity, assess fire extent, and highlight pre-fire tree density and land cover. The study focuses on the catastrophic fire in the Evros region and the damage to the National Forest Park of Dadia–Lefkimmi–Soufli. It also analyzes significant fires in Rhodes, Attica, Thessaly, Evia, Corfu, and Magnesia, emphasizing the compounded challenges posed by terrain, climate, and human factors in those areas. Additionally, the climate data for each affected area were compared with the weather conditions prevailing at the time of the fires. Copernicus Land Cover and Tree Density data are integrated to aid future management, assessment, and restoration. The analysis of maps and fire statistics underscores a notable pattern: areas with higher pre-fire tree density experienced correspondingly higher burn severity. This research underscores the crucial role of such data in assessing wildfire impact. In addition, compared with Copernicus Emergency Management Service, the burned area maps validate the accuracy and reliability of the utilized satellite data. The total burned area was assessed with a high accuracy rate of 96.28%. [ABSTRACT FROM AUTHOR]

Aims: We assessed the mental health effects of Australia's 2019–2020 bushfires 12–18 months later, predicting psychological distress and positive psychological outcomes from bushfire exposure and a range of demographic variables, and seeking insights to enhance disaster preparedness and resilience planning for different profiles of people. Methods: We surveyed 3083 bushfire-affected and non-affected Australian residents about their experiences of bushfire, COVID-19, psychological distress (depression, anxiety, stress, post-traumatic stress disorder) and positive psychological outcomes (resilient coping, wellbeing). Results: We found high rates of distress across all participants, exacerbated by severity of bushfire exposure. For people who were bushfire-affected, being older, having less financial stress, and having no or fewer pre-existing mental disorders predicted both lower distress and higher positive outcomes. Being male or having less income loss also predicted positive outcomes. Severity of exposure, higher education and higher COVID-19-related stressors predicted both higher distress and higher positive outcomes. Pre-existing physical health diagnosis and previous bushfire experience did not significantly predict distress or positive outcomes. Recommendations: To promote disaster resilience, we recommend investment in mental health, particularly for younger adults and for those in rural and remote areas. We also recommend investment in mechanisms to protect against financial distress and the development of a broader definition of bushfire-related impacts than is currently used to capture brushfires' far-reaching effects. [ABSTRACT FROM AUTHOR]

In 2022, prolonged periods of extreme heat waves fueled huge wildfires across the globe. While research has shown that past experience with wildfire increases homeowners' intentions to adopt fire mitigation activities, little is known about whether the impact of disaster can be long-lasting and represent a stable behavioral change. Thus, the current work explored whether Chinese homeowners' intentions to perform fire wise actions would change over time. In Study 1, we compared responses of residents in a fire-stricken area with those of residents in a nondisaster area three days after a massive wildfire. It was found that participants who had just experienced a wildfire reported a stronger intent to take fire mitigation on both self-report and behavioral measures. Study 2 involved a follow-up survey that took place in the same areas one month after the fire had occurred. The results showed that participants in these two areas demonstrated no differences in intentions to implement fire mitigation measures, which suggests that the impact of disasters decayed over time. Combined, these findings suggest that past experience with wildfire will likely give rise to stronger intention to engage in mitigation behavior but this effect may diminish with time ticking away. [ABSTRACT FROM AUTHOR]

Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The results are in good agreement with observations recorded during the event. Extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making and emergency response management during wildfire events. [ABSTRACT FROM AUTHOR]

Purpose: Healthcare staff are on the frontline during disasters despite any personal adversity and vicarious trauma they may be experiencing. Wellness Warrior training is a post-disaster intervention developed in response to the 2019-2020 Australian bushfires to support staff in a rural hospital located on the South Coast of New South Wales, Australia. Method: This study explored the experiences and perspectives of 18 healthcare staff who were trained to provide emotional and peer support to their colleagues in the aftermath of a crisis. All the Wellness Warriors participated in semi-structured interviews between March and April 2020. Data were analysed using the reflexive thematic approach. Results: Healthcare staff reported developing interpersonal skills around deep listening and connecting with others which allowed for hearing the core of their colleagues' concerns. The training also helped staff to feel differently about work and restored their faith in healthcare leadership. Conclusion: Wellness Warrior training provided staff with knowledge and skills to support their colleagues in the aftermath of a natural disaster and later during the COVID-19 pandemic. As such, these findings suggest that peer support programs such as Wellness Warriors could be one way healthcare organisations can attempt to alleviate the psychological impact of natural disasters. [ABSTRACT FROM AUTHOR]

During an unprecedented crisis of bushfires, the staff of emergency management control centers in southeast Australia pause to perform rites with their political leaders. They reenact decisions that have already been made and generate divinations of fiery futures that are unlikely to occur. Their work, like that of others in large centralized technical infrastructures, is made possible by ritualized structures and practices that constitute a double bind. Emergency managers know their performances of control over open systems will inevitably fail to command the world's hazardous surprises. Yet they must maintain these performances, even though they create impossible expectations and forestall self‐critique or desired transformations. Attending to this situation, these sites, and their inhabitants reveals persistent attachments to systems of control in our late‐industrial age and changing climate. [ABSTRACT FROM AUTHOR]

Australia has been grappling with recurring bushfires for over a century, significantly affecting the landscape and communities. Despite this, there has been an increase in residents moving into high-risk bushfire areas. This study aimed to develop a framework that could guide householder decisionmaking regarding self-evacuation during bushfires by identifying the incentives that encourage early evacuation. The study used a qualitative approach and 30 semi-structured interviews were conducted with residents in the southeast part of New South Wales; a region hardest hit during the 2019–20 summer bushfire season. Thirteen potential incentives that motivate self-evacuation were identified. The framework provides valuable insights into how incentives could influence residents’ decision-making during bushfires. In addition, it serves as a useful reference for policymakers, fire services and emergency management organisations when creating effective ways to encourage early self-evacuation and, ultimately, reduce injury and fatality. [ABSTRACT FROM AUTHOR]

Wildland fires, a natural calamity, pose a significant threat to both human lives and the environment while causing extensive economic damage. As the use of Unmanned Aerial Vehicles (UAVs) with computer vision in disaster management continues to grow, there is a rising need for effective wildfire classification and localization. We propose a multi-stream hybrid deep learning model with a dual-stream attention mechanism for classifying wildfires from aerial and territorial images. Our proposed method incorporates a pre-trained EfficientNetB7 and customized Attention Connected Network (ACNet). This approach demonstrates exceptional classification performance on two widely recognized benchmark datasets. Bayesian optimization is employed for the purpose of refining and optimizing the hyperparameters of the model. The proposed model attains 97.45%, 98.20%, 97.10%, and 97.12% as accuracy, precision, recall, and F1-score, respectively, on the FLAME dataset. Moreover, while evaluated on the DeepFire dataset, the model achieves accuracy, precision, recall, and F1-scores of 95.97%, 95.19%, 96.01%, and 95.54%, respectively. The proposed method achieved a TNR of 95.5% and a TPR of 99.3% on the FLAME dataset, as well as a TNR of 94.47% and a TPR of 96.82% on the DeepFire dataset. This performance surpasses numerous state-of-the-art methods. To demonstrate the interpretability of our model, we incorporated the GRAD-CAM technique, which enables us to precisely identify the fire location within the feature map. This finding illustrates the efficacy of the model in accurately categorizing wildfires, even in areas with less fire activity. [ABSTRACT FROM AUTHOR]

Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to 10 understand the drivers of this devastating event. The results are in good agreement with observations recorded during the event. Extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making and emergency response management during wildfire events. [ABSTRACT FROM AUTHOR]

This study aims to assess whether two publicly available sources of fire threats to 346 Cultural World Heritage Sites across Europe substitute or complement each other. By doing so, a novel measure based on information from the UNESCO periodic report II is created and benchmarked against the European forest fire information system (EFFIS) index. The UNESCO periodic report shows that forest fires are perceived as an actual or foreseeable hazard by 40% of the management of Cultural World Heritage Sites in Europe. When the EFFIS index is linked to the UNESCO World Heritage database, it occurs that 48% of these sites are at high risk of fire, 31% at medium risk and 21% at low risk. Results based on Probit and Fractional Probit estimations reveal that the perceived fire risk relates to several site characteristics as well as location. The regressions using the EFFIS index as dependent variable show indifference to site characteristics even if location is of importance. Estimations give that the perceived fire risk is highest for sites in the East and the North of Europe, while the results for the EFFIS index lead to a dominant risk in the South. A 10° increase in latitude (corresponding to the distances between Vienna and Stockholm or Athens and Vienna) leads to a considerable decrease in the proportion of high fire risk by 28 percentage points (with a sample mean of 48%). Thus, the two measures of fire risks complement rather than substitute each other. Latitude is of no importance for the site managers, although the EFFIS gives this aspect a heavy weight, with low or zero risks in locations at higher latitudes (Iceland, Ireland, Latvia, and Norway) and larger risks in Southern Europe (Cyprus, Malta, Portugal, Albania, Spain, and Greece). In addition, the perception of (wild)-fire threat is significantly lower for cities. [ABSTRACT FROM AUTHOR]