An integrated approach for mapping fire suppression difficulty in three different ecosystems of Eastern Europe

Mitsopoulos, Ioannis; Mallinis, Giorgos; Zibtsev, Sergiy; Yavuz, Mehmet; Sağlam, Bülent; Küçük, Ömer; Bogomolov, V. V.; Borsuk, A.; Zaimes, George Ν.

doi:10.1080/14498596.2016.1169952

Cited by 19 publications

(11 citation statements)

References 39 publications

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“…Operational decision support systems usually integrate real‐time fire predictions with the location of valued resources and assets to assist firefighting (Calkin, Thompson, Finney, & Hyde, 2011; O'Connor, Thompson, & y Silva, 2016). Specifically, fire simulation modeling provides a set of fire spread and intensity outputs based on the weather forecast in the following days, and then this information is assembled with cartographic sources showing the main transport network and urban settlements in order to guide the deployment of suppression resources (Calkin, Finney, Ager, Thompson, & Gebert, 2011; Mitsopoulos et al., 2017). Accordingly, predicting where we can restrict fire growth is decisive, and current decision support systems aim to integrate estimates of wildfire containment probability (Wei, Thompson, Scott, O'Connor, & Dunn, 2019).…”

Section: Introductionmentioning

confidence: 99%

Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region

et al. 2020

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Despite escalating expenditures in firefighting, extreme fire events continue to pose a major threat to ecosystem services and human communities in Mediterranean areas. Developing a safe and effective fire response is paramount to efficiently restrict fire spread, reduce negative effects to natural values, prevent residential housing losses, and avoid causalties. Though current fire policies in most countries demand full suppression, few studies have attempted to identify the strategic locations where firefighting efforts would likely contain catastrophic fire events. The success in containing those fires that escape initial attack is determined by diverse structural factors such as ground accessibility, airborne support, barriers to surface fire spread, and vegetation impedance. In this study, we predicted the success in fire containment across Catalonia (northeastern Spain) using a model generated with random forest from detailed geospatial data and a set of 73 fire perimeters for the period 2008-2016. The model attained a high predictive performance (AUC = 0.88), and the results were provided at fine resolution (25 m) for the entire study area (32,108 km 2). The highest success rates were found in agricultural plains along the nonburnable barriers such as major road corridors and largest rivers. Low levels of containment likelihood were predicted for dense forest lands and steep-relief mountainous areas. The results can assist in suppression resource pre-positioning and extended attack decision making, but also in strategic fuels management oriented at creating defensive locations and fragmenting the landscape in operational firefighting areas. Our modeling workflow and methods may serve as a baseline to generate locally adapted models in fire-prone areas elsewhere.

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Section: Introductionmentioning

confidence: 99%

Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region

et al. 2020

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“…Although several models have been established for basic fire behaviour research or for emergency response, only a handful have been designed for fuel management planning (Ager et al 2011). Models created for fire behavior simulation in United States, Canada and Australia are also widely used in Europe (Mitsopoulos et al 2017), becoming popular for prescribed fires. However, many aspects should be analyzed to reveal possible differences between wildfire and prescribed fire modelling.…”

Section: Introductionmentioning

confidence: 99%

Cellular Automata Based Simulators for the Design of Prescribed Fire Plans: the Case Study of Liguria, Italy

Perello,

Trucchia,

Baghino

et al. 2023

Preprint

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Background Socio-economic changes of the last decades have led to fuel buildup in Mediterranean forests. In the context of Climate Change, this situation has resulted in the formation of potential fire traps that could lead to catastrophic events. Several wildfire management systems have therefore started to use prescribed fires for land management and wildfire risk mitigation. Prescribed fires are prepared by designing a plan, where specific objectives are identified, prescriptions are checked, and scenarios are defined. In the plan definition phase, simulation models can provide an additional decision-support tool, allowing the different scenarios to be qualitatively and quantitatively assessed. We used the well-established wildfire simulation tool PROPAGATOR to identify potential areas of treatment and to assess different scenarios of hypothetical prescribed fires. In the present work, we prepared the model for use in prescribed fires by changing the native space-time resolution to a finer scale. We selected a case study in the Liguria region, Italy, where the model is operationally used by the regional wildfire risk management system during emergencies. Results We first used the propagation model to simulate a wildfire event, to show the potentiality of the model as an emergency response tool. We selected the most important fire incident that occurred in the Liguria region in 2022. We then used PROPAGATOR to identify the optimal treatment areas to maximize wildfire risk mitigation effects and reduce the costs of treatment. In the identified areas, we used the model to simulate ignition scenarios in different weather conditions allowed by the regional regulation. The scenarios developed by the model made it possible to differentiate between situations that are under control and those that pose greater risks. Conclusions We showed how PROPAGATOR can provide quantitative and qualitative information that can be used in prescribed fire planning. Our methodology involved incorporating expert opinions throughout the process and providing scenarios based on this information. The possibility of evaluating different scenarios and having quantitative information helps make informed decisions, promoting safer and more efficient fire management practices.

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“…In recent years, the fire science community has developed a wide range of operationally focused assessment and planning tools. This body of work includes various risk assessment tools to estimate the social and ecological consequences of fire [29][30][31][32][33]; models of suppression difficulty, resistance to control, and potential fire control locations that speak to firefighting challenges and opportunities [34][35][36][37][38]; and models of fire responder safety zones, escape routes, and falling tree (snag) hazards to help suppression resources avoid harm [39][40][41][42]. Despite the proliferation of risk-based information, its use in fire management and decision support remains limited in part due to the lack of attention paid towards engineering the delivery and communication of this information to key users and decision makers [43,44].…”

Section: Introductionmentioning

confidence: 99%

Prototyping a Geospatial Atlas for Wildfire Planning and Management

Thompson

Gannon

Caggiano

et al. 2020

Forests

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Wildland fire managers are increasingly embracing risk management principles by being more anticipatory, proactive, and “engaging the fire before it starts”. This entails investing in pre-season, cross-boundary, strategic fire response planning with partners and stakeholders to build a shared understanding of wildfire risks and management opportunities. A key innovation in planning is the development of potential operational delineations (PODs), i.e., spatial management units whose boundaries are relevant to fire containment operations (e.g., roads, ridgetops, and fuel transitions), and within which potential fire consequences, suppression opportunities/challenges, and strategic response objectives can be analyzed to inform fire management decision making. As of the summer of 2020, PODs have been developed on more than forty landscapes encompassing National Forest System lands across the western USA, providing utility for planning, communication, mitigation prioritization, and incident response strategy development. Here, we review development of a decision support tool—a POD Atlas—intended to facilitate cross-boundary, collaborative strategic wildfire planning and management by providing high-resolution information on landscape conditions, values at risk, and fire management resource needs for individual PODs. With the atlas, users can rapidly access and assimilate multiple forms of pre-loaded data and analytics in a customizable manner. We prototyped and operationalized this tool in concert with, and for use by, fire managers on several National Forests in the Southern Rocky Mountains of the USA. We present examples, discuss real-world use cases, and highlight opportunities for continued decision support improvement.

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An integrated approach for mapping fire suppression difficulty in three different ecosystems of Eastern Europe

Cited by 19 publications

References 39 publications

Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region

Geospatial Modeling of Containment Probability for Escaped Wildfires in a Mediterranean Region

Cellular Automata Based Simulators for the Design of Prescribed Fire Plans: the Case Study of Liguria, Italy

Prototyping a Geospatial Atlas for Wildfire Planning and Management

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