Relevant bibliographies by topics / Wildfire simulation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Wildfire simulation'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Wildfire simulation"

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Ott, Cory W., Bishrant Adhikari, Simon P. Alexander, Paddington Hodza, Chen Xu, and Thomas A. Minckley. "Predicting Fire Propagation across Heterogeneous Landscapes Using WyoFire: A Monte Carlo-Driven Wildfire Model." Fire 3, no. 4 (December 11, 2020): 71. http://dx.doi.org/10.3390/fire3040071.

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The scope of wildfires over the previous decade has brought these natural hazards to the forefront of risk management. Wildfires threaten human health, safety, and property, and there is a need for comprehensive and readily usable wildfire simulation platforms that can be applied effectively by wildfire experts to help preserve physical infrastructure, biodiversity, and landscape integrity. Evaluating such platforms is important, particularly in determining the platforms’ reliability in forecasting the spatiotemporal trajectories of wildfire events. This study evaluated the predictive performance of a wildfire simulation platform that implements a Monte Carlo-based wildfire model called WyoFire. WyoFire was used to predict the growth of 10 wildfires that occurred in Wyoming, USA, in 2017 and 2019. The predictive quality of this model was determined by comparing disagreement and agreement areas between the observed and simulated wildfire boundaries. Overestimation–underestimation was greatest in grassland fires (>32) and lowest in mixed-forest, woodland, and shrub-steppe fires (<−2.5). Spatial and statistical analyses of observed and predicted fire perimeters were conducted to measure the accuracy of the predicated outputs. The results indicate that simulations of wildfires that occurred in shrubland- and grassland-dominated environments had the tendency to over-predict, while simulations of fires that took place within forested and woodland-dominated environments displayed the tendency to under-predict.
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Salis, Michele, Alan A. Ager, Bachisio Arca, Mark A. Finney, Valentina Bacciu, Pierpaolo Duce, and Donatella Spano. "Assessing exposure of human and ecological values to wildfire in Sardinia, Italy." International Journal of Wildland Fire 22, no. 4 (2013): 549. http://dx.doi.org/10.1071/wf11060.

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We used simulation modelling to analyse spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational values and highly valued agricultural areas that are increasingly being threatened by severe wildfires. Historical fire data and wildfire simulations were used to estimate burn probabilities, flame length and fire size. We examined how these risk factors varied among and within highly valued features located on the island. Estimates of burn probability excluding non-burnable fuels, ranged from 0–1.92 × 10–3, with a mean value of 6.48 × 10–5. Spatial patterns in modelled outputs were strongly related to fuel loadings, although topographic and other influences were apparent. Wide variation was observed among the land parcels for all the key values, providing a quantitative approach to inform wildfire risk management activities.
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Kelso, Joel K., Drew Mellor, Mary E. Murphy, and George J. Milne. "Techniques for evaluating wildfire simulators via the simulation of historical fires using the AUSTRALIS simulator." International Journal of Wildland Fire 24, no. 6 (2015): 784. http://dx.doi.org/10.1071/wf14047.

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A methodology for validating fire spread simulation systems using historical fire data is presented. The key features of this methodology are (a) quantitative comparison between simulator-generated fire perimeters and fire perimeters from an independently produced fire reconstruction at multiple time points during the fire, and (b) extensive sensitivity analyses on simulation variables including simulation spatial resolution, weather, vegetation coverage and fire behaviour model selection to determine the effect of each simulation input on the simulation output. The methodology is demonstrated in a case study in which the ability of the Australis high-performance wildfire simulator to replicate a large wildfire in Western Australia was examined. Simulation accuracy was found to be lower in extreme fire danger conditions and exhibited under-prediction of the head fire rate of spread. This was caused by inaccuracies in at least one of wind speed data, vegetation data or the fire behaviour model applied; however, the source of the inaccuracy could not be further diagnosed with the available data. The gathering of accurate data during and after active wildfires would facilitate more rigorous simulator and fire behaviour model validation studies as well as more accurate prediction of ‘live’ wildfires.
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Parisien, Marc-André, Denyse A. Dawe, Carol Miller, Christopher A. Stockdale, and O. Bradley Armitage. "Applications of simulation-based burn probability modelling: a review." International Journal of Wildland Fire 28, no. 12 (2019): 913. http://dx.doi.org/10.1071/wf19069.

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Wildland fire scientists and land managers working in fire-prone areas require spatial estimates of wildfire potential. To fulfill this need, a simulation-modelling approach was developed whereby multiple individual wildfires are modelled in an iterative fashion across a landscape to obtain location-based measures of fire likelihood and fire behaviour (e.g. fire intensity, biomass consumption). This method, termed burn probability (BP) modelling, takes advantage of fire spread algorithms created for operational uses and the proliferation of available data representing wildfire patterns, fuels and weather. This review describes this approach and provides an overview of its applications in wildland fire research, risk analysis and land management. We broadly classify the application of BP models as (1) direct examination, (2) neighbourhood processes, (3) fire hazard and risk and (4) integration with secondary models. Direct examination analyses are those that require no further processing of model outputs; they range from a simple visual examination of outputs to an assessment of alternate states (i.e. scenarios). Neighbourhood process analyses examine patterns of fire ignitions and subsequent spread across land designations. Fire hazard combines fire probability and a quantitative assessment of fire behaviour, whereas risk is the product of fire likelihood and potential impacts of wildfire. The integration with secondary models represents situations where BP model outputs are integrated into, or used in conjunction with, other models or modelling platforms.
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Filippi, Jean-Baptiste, Vivien Mallet, and Bahaa Nader. "Representation and evaluation of wildfire propagation simulations." International Journal of Wildland Fire 23, no. 1 (2014): 46. http://dx.doi.org/10.1071/wf12202.

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This paper provides a formal mathematical representation of a wildfire simulation, reviews the most common scoring methods using this formalism, and proposes new methods that are explicitly designed to evaluate a forest fire simulation from ignition to extinction. These scoring or agreement methods are tested with synthetic cases in order to expose strengths and weaknesses, and with more complex fire simulations using real observations. An implementation of the methods is provided as well as an overview of the software package. The paper stresses the importance of scores that can evaluate the dynamics of a simulation, as opposed to methods relying on snapshots of the burned surfaces computed by the model. The two new methods, arrival time agreement and shape agreement, take into account the dynamics of the simulation between observation times. Although no scoring method is able to perfectly synthesise a simulation error in a single number, the analysis of the scores obtained on idealised and real simulations provides insights into the advantages of these methods for the evaluation of fire dynamics.
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McEvoy, Andy, Max Nielsen-Pincus, Andrés Holz, Arielle J. Catalano, and Kelly E. Gleason. "Projected Impact of Mid-21st Century Climate Change on Wildfire Hazard in a Major Urban Watershed outside Portland, Oregon USA." Fire 3, no. 4 (December 8, 2020): 70. http://dx.doi.org/10.3390/fire3040070.

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Characterizing wildfire regimes where wildfires are uncommon is challenged by a lack of empirical information. Moreover, climate change is projected to lead to increasingly frequent wildfires and additional annual area burned in forests historically characterized by long fire return intervals. Western Oregon and Washington, USA (westside) have experienced few large wildfires (fires greater than 100 hectares) the past century and are characterized to infrequent large fires with return intervals greater than 500 years. We evaluated impacts of climate change on wildfire hazard in a major urban watershed outside Portland, OR, USA. We simulated wildfire occurrence and fire regime characteristics under contemporary conditions (1992–2015) and four mid-century (2040–2069) scenarios using Representative Concentration Pathway (RCP) 8.5. Simulated mid-century fire seasons expanded in most scenarios, in some cases by nearly two months. In all scenarios, average fire size and frequency projections increased significantly. Fire regime characteristics under the hottest and driest mid-century scenarios illustrate novel disturbance regimes which could result in permanent changes to forest structure and composition and the provision of ecosystem services. Managers and planners can use the range of modeled outputs and simulation results to inform robust strategies for climate adaptation and risk mitigation.
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Hoang, Roger V., Matthew R. Sgambati, Timothy J. Brown, Daniel S. Coming, and Frederick C. Harris. "VFire: Immersive wildfire simulation and visualization." Computers & Graphics 34, no. 6 (December 2010): 655–64. http://dx.doi.org/10.1016/j.cag.2010.09.014.

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Benali, Akli, Ana C. L. Sá, João Pinho, Paulo M. Fernandes, and José M. C. Pereira. "Understanding the Impact of Different Landscape-Level Fuel Management Strategies on Wildfire Hazard in Central Portugal." Forests 12, no. 5 (April 23, 2021): 522. http://dx.doi.org/10.3390/f12050522.

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The extreme 2017 fire season in Portugal led to widespread recognition of the need for a paradigm shift in forest and wildfire management. We focused our study on Alvares, a parish in central Portugal located in a fire-prone area, which had 60% of its area burned in 2017. We evaluated how different fuel treatment strategies may reduce wildfire hazard in Alvares through (i) a fuel break network with different extents corresponding to different levels of priority and (ii) random fuel treatments resulting from a potential increase in stand-level management intensity. To assess this, we developed a stochastic wildfire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast and center-east areas of the parish that are very often associated with high fireline intensities. The different fuel treatment scenarios decreased burned area between 12.1–31.2%, resulting from 1–4.6% increases in the annual treatment area and reduced the likelihood of wildfires larger than 5000 ha by 10–40%. On average, simulated burned area decreased 0.22% per each ha treated, and cost-effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.
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Prestemon, Jeffrey P., David T. Butry, and Douglas S. Thomas. "The net benefits of human-ignited wildfire forecasting: the case of tribal land units in the United States." International Journal of Wildland Fire 25, no. 4 (2016): 390. http://dx.doi.org/10.1071/wf15128.

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Research shows that some categories of human-ignited wildfires may be forecastable, owing to their temporal clustering, with the possibility that resources could be predeployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an autoregressive conditional Poisson model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared with alternatives, and the simplest of the autoregressive conditional Poisson models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law-enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires.
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Xofis, Panteleimon, Pavlos Konstantinidis, Iakovos Papadopoulos, and Georgios Tsiourlis. "Integrating Remote Sensing Methods and Fire Simulation Models to Estimate Fire Hazard in a South-East Mediterranean Protected Area." Fire 3, no. 3 (July 19, 2020): 31. http://dx.doi.org/10.3390/fire3030031.

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Unlike low intensity fire which promotes landscape heterogeneity and important ecosystem services, large high-intensity wildfires constitute a significant destructive factor despite the increased amount of resources allocated to fire suppression and the improvement of firefighting tactics and levels of organization. Wildfires also affect properties, while an increasing number of fatalities are also associated with wildfires. It is now widely accepted that an effective wildfire management strategy can no longer rely on fire suppression alone. Scientific advances on fire behavior simulation and the increasing availability of remote sensing data, along with advanced systems of fire detection can significantly reduce fire hazards. In the current study remote sensing data and methods, and fire behavior simulation models are integrated to assess the fire hazard in a protected area of the southeast Mediterranean region and its surroundings. A spatially explicit fire hazard index was generated by combining fire intensity estimations and proxies of fire ignition probability. The results suggest that more than 50% of the study area, and the great majority of the protected area, is facing an extremely high hazard for a high-intensity fire. Pine forest formations, characterized by high flammability, low canopy base height and a dense shrub understory are facing the most critical hazard. The results are discussed in relation to the need for adopting an alternative wildfire management strategy.
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Dissertations / Theses on the topic "Wildfire simulation"

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Dunn, Adam. "A model of wildfire propagation using the interacting spatial automata formalism." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0071.

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[Truncated abstract] In this thesis, I address the modelling and computer simulation of spatial, eventdriven systems from a computer science perspective. Spatially explicit models of wildland fire (wildfire) behaviour are addressed as the specific application domain. Wildfire behaviour is expressed as a formal model and the associated simulations are compared to existing models and implementations. It is shown that the in- teracting spatial automata formalism provides a general framework for modelling spatial event-driven systems and is appropriate to wildfire systems. The challenge adressed is that of physically realistic modelling of wildfire behaviour in heterogeneous environments . . . Many current models do not incorporate the influence of a neighbourhood (the geometry of the fire front local to an unburnt volume of fuel, for example), but rather determine the propagation of fire using only point information. Whilst neighbourhood-based influence of behaviour is common to cellular automata theory, its use is very rare in existing models of wildfire models. In this thesis, I present the modelling technique and demonstrate its applicability to wildfire systems via a series of simulation experiments, where I reproduce known spatial wildfire dynamics. I conclude that the interacting spatial automata formalism is appropriate as a basis for constructing new computer simulations of wildfire spread behaviour. Simulation results are compared to existing implementations, highlighting the limitations of current models and demonstrating that the new models are capable of greater physical realism.
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Hoang, Roger Viet. "Wildfire simulation on the GPU." abstract and full text PDF (UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1460762.

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Gu, Feng. "Dynamic Data Driven Application System for Wildfire Spread Simulation." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/cs_diss/57.

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Wildfires have significant impact on both ecosystems and human society. To effectively manage wildfires, simulation models are used to study and predict wildfire spread. The accuracy of wildfire spread simulations depends on many factors, including GIS data, fuel data, weather data, and high-fidelity wildfire behavior models. Unfortunately, due to the dynamic and complex nature of wildfire, it is impractical to obtain all these data with no error. Therefore, predictions from the simulation model will be different from what it is in a real wildfire. Without assimilating data from the real wildfire and dynamically adjusting the simulation, the difference between the simulation and the real wildfire is very likely to continuously grow. With the development of sensor technologies and the advance of computer infrastructure, dynamic data driven application systems (DDDAS) have become an active research area in recent years. In a DDDAS, data obtained from wireless sensors is fed into the simulation model to make predictions of the real system. This dynamic input is treated as the measurement to evaluate the output and adjust the states of the model, thus to improve simulation results. To improve the accuracy of wildfire spread simulations, we apply the concept of DDDAS to wildfire spread simulation by dynamically assimilating sensor data from real wildfires into the simulation model. The assimilation system relates the system model and the observation data of the true state, and uses analysis approaches to obtain state estimations. We employ Sequential Monte Carlo (SMC) methods (also called particle filters) to carry out data assimilation in this work. Based on the structure of DDDAS, this dissertation presents the data assimilation system and data assimilation results in wildfire spread simulations. We carry out sensitivity analysis for different densities, frequencies, and qualities of sensor data, and quantify the effectiveness of SMC methods based on different measurement metrics. Furthermore, to improve simulation results, the image-morphing technique is introduced into the DDDAS for wildfire spread simulation.
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Tasel, Erdinc. "Gis-based Spatial Model For Wildfire Simulation: Marmaris &amp." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/3/1017821/index.pdf.

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Each year many forest fires have occurred and huge amount of forest areas in each country have been lost. Turkey like many world countries have forest fire problem. 27 % of Turkey&
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s lands are covered by forest and 48 % of these forest areas are productive, however 52 % of them must be protected. There occurred 21000 forest fires due to several reasons between 1993 and 2002. It is estimated that 23477 ha area has been destroyed annually due to wildfires. The fire management strategies can be built on the scenarios derived from the simulation processes. In this study a GIS &
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based fire simulating model is used to simulate a past fire occurred in Marmaris &
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etibeli, Turkey, in August 2002. This model uses Rothermel&
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s surface fire model, Rothermel&
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s and Van Wagner&
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s crown fire model and Albini&
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s torching tree model. The input variables required by the model can be divided into four groups: fuel type, fuel moisture, topography and wind. The suitable fuel type classification of the vegetation of the study area has been performed according to the Northern Forest Fire Laboratory (NFFL) Fuel Model. The fuel moisture data were obtained from the experts working in the General Directorate of Forestry. The fire spread pattern was derived using two IKONOS images representing the pre- and post-fire situations by visual interpretation. Time of arrival, the rate of spread and the spread direction of the fire were obtained as the output and 70 % of the burned area was estimated correctly from the fire simulating model.
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Song, Fei. "An Interactive Wildfire Spread and Suppression Simulation Environment Based on Devs-Fire." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/cs_theses/59.

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Wildfires pose serious threats to the society and environment. Simulation of wildfire spread and fire suppression remains a challenging task due to the complexity of wildfire behavior and fire suppression tactics. In previous work, a wildfire spread and suppression simulation model called DEVS-FIRE has been developed. Based on that model, this thesis develops a graphic user interface to support an interactive simulation environment for surface wildfire spread and suppression simulation. The developed environment allows users to dynamically set up fire spread simulations, and to interacticaly deploy firefighting agents to experiment different fire suppression tactics. This graphic user interface is implemented using the Java Swing framework, and is intergrated with the DEVS-FIRE model in a well-designed manner. The software architecture is described and the simulation environment and experiment results with different fuel, terrain and weather data are presented.
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Guo, Song. "Simulation Software as a Service and Service-Oriented Simulation Experiment." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/cs_diss/69.

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Simulation software is being increasingly used in various domains for system analysis and/or behavior prediction. Traditionally, researchers and field experts need to have access to the computers that host the simulation software to do simulation experiments. With recent advances in cloud computing and Software as a Service (SaaS), a new paradigm is emerging where simulation software is used as services that are composed with others and dynamically influence each other for service-oriented simulation experiment on the Internet. The new service-oriented paradigm brings new research challenges in composing multiple simulation services in a meaningful and correct way for simulation experiments. To systematically support simulation software as a service (SimSaaS) and service-oriented simulation experiment, we propose a layered framework that includes five layers: an infrastructure layer, a simulation execution engine layer, a simulation service layer, a simulation experiment layer and finally a graphical user interface layer. Within this layered framework, we provide a specification for both simulation experiment and the involved individual simulation services. Such a formal specification is useful in order to support systematic compositions of simulation services as well as automatic deployment of composed services for carrying out simulation experiments. Built on this specification, we identify the issue of mismatch of time granularity and event granularity in composing simulation services at the pragmatic level, and develop four types of granularity handling agents to be associated with the couplings between services. The ultimate goal is to achieve standard and automated approaches for simulation service composition in the emerging service-oriented computing environment. Finally, to achieve more efficient service-oriented simulation, we develop a profile-based partitioning method that exploits a system’s dynamic behavior and uses it as a profile to guide the spatial partitioning for more efficient parallel simulation. We develop the work in this dissertation within the application context of wildfire spread simulation, and demonstrate the effectiveness of our work based on this application.
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Penick, Michael Alan. "VFIRE virtual fire in realistic environments : a framework for wildfire visualization in immersive environments /." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1442845.

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Bailon-Ruiz, Rafael. "Design of a wildfire monitoring system using fleets of Unmanned Aerial Vehicles." Thesis, Toulouse, INSA, 2020. http://www.theses.fr/2020ISAT0011.

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Les feux de forêt sont des incendies de végétation incontrôlés qui causent des dégâts importants à l’environnement, aux biens et aux personnes. Les actions de lutte contre de tels feux sont risqués et peuvent par conséquent bénéficier de techniques d'automatisation pour réduire l’exposition humaine. La télédétection aérienne est une technique qui permet d’obtenir des informations précises sur l’état d'un feu de forêt, afin que les équipes d’intervention puissent préparer des contre-mesures. Avec des véhicules aériens habités, elle expose les opérateurs à des risques élevés, qui peuvent être évités par l’utilisation de véhicules autonomes. Cette thèse présente un système de surveillance de feux de forêt basé sur des flottes de véhicules aériens sans pilote (UAV) afin de fournir aux pompiers des renseignements précis et à jour sur un feu de forêt. Nous présentons une approche pour planifier les trajectoires d’une flotte de drones à voilure fixe afin d’observer un feu de forêt évoluant au fil du temps. Des modèles réalistes du terrain, du processus de propagation du feu et des drones sont exploités, ainsi qu’un modèle du vent, pour prédire la propagation des feux de forêt et planifier le mouvement des drones. L’approche présentée adapte une méthode générique de recherche à voisinage variable (VNS) à ces modèles et les contraintes associées. L’exécution de la mission d’observation planifiée fournit des cartes des feux de forêt qui sont transmises à l’équipe d’intervention et exploitées par l’algorithme de planification pour déterminer de nouvelles trajectoires d’observation. Les algorithmes et les modèles sont intégrés dans une architecture logicielle permettant l’exécution dans des scénarios avec différents niveaux de réalisme, avec des drones réels et simulés survolant un feu de forêt réel ou synthétique. Les résultats de simulation mixte montrent la capacité de planifier les trajectoires d’observation d’une petite flotte de drones et de mettre à jour les plans lorsque de nouvelles informations sur l’incendie sont incorporées dans le modèle de propagation de feu
Wildfires, also known as forest or wildland fires, are uncontrolled vegetation fires occurring in rural areas that cause tremendous damage to the society, harming environment, property and people. The firefighting endeavor is a dull, dirty and dangerous job and as such, can greatly benefit from automation to reduce human exposure to hazards. Aerial remote sensing is a common technique to obtain precise information about a wildfire state so fire response teams can prepare countermeasures. This task, when performed with manned aerial vehicles, expose operators to high risks that can be eliminated by the use of autonomous vehicles. This thesis introduces a wildfire monitoring system based on fleets of unmanned aerial vehicles (UAVs) to provide firefighters with timely updated information about a wildland fire. We present an approach to plan trajectories for a fleet of fixed-wing UAVs to observe a wildfire evolving over time. Realistic models of the terrain, of the fire propagation process, and of the UAVs are exploited, together with a model of the wind, to predict wildfire spread and plan UAV motion. The approach tailors a generic Variable Neighborhood Search method to these models and the associated constraints. The execution of the planned monitoring mission provides wildfire maps that are transmitted to the fire response team and exploited by the planning algorithm to plan new observation trajectories. Algorithms and models are integrated within a software architecture allowing for execution under scenarios with different levels of realism, with real and simulated UAVs flying over a real or synthetic wildfire. Mixed-reality simulation results show the ability to plan observation trajectories for a small fleet of UAVs, and to update the plans when new information on the fire are incorporated in the fire model
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Kloninger, Paul. "MDO-Simulation eines Rutschreifens auf GFK-Wasserrutschen." Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-206945.

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Die Option Mechanism Dynamics (MDO) von Creo Parametric ist ein Tool aus dem Bereich Starrkörperdynamik. Im Kern des Vortrags steht jedoch die MDO-Funktion 3D-Kontakt, die einzigartig mit elastischen Körpern arbeitet. Im Vortrag wird die Vorgehensweise bei der dynamischen Simulation eines Rutschreifens auf GFK-Wasserrutschen erläutert, abschließend werden Animationsbeispiele präsentiert.
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Kessels, Henricus. "Wildfire Management in the Southside Region of Canada’s Montane Cordillera - A Systems Modelling Application on Firebreak Strategies." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35107.

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There is growing recognition of the importance of preserving Canada’s forests. Canada’s 348 million hectares of forest land cover 35% of its land area, representing 9% of the world’s forests and 24% of the world’s boreal forests. As a renewable resource, forests offer significant environmental, economic and recreational benefits and innumerable services contributing to the quality of life. Canada has recently entered an era of increased frequency and severity of natural disasters. Ecosystems and communities especially in western Canada have recently undergone a trend of increasing pressures from natural disturbances. These disturbances include wildfires associated with increased fuel load levels from past fire suppression regimes and a widely spread infestation of the mountain pine beetle in addition to changes in weather patterns. Wildfire activity has reached extreme levels in many of the recent years. This thesis profiles an area of western Canada within the Montane Cordillera covering the Nechako Lakes Electoral District in central British Columbia and assesses its vulnerability to the specific hazard of wildfires caused by natural and man-made sources. The objectives of this research are to review, simulate and assess the impact of various fuel management strategies in a sub-section of the Nechako Lakes Electoral District called the Southside. Values at risk include private property and old growth forest in respectively timber supply areas, provincial parks, woodlots and community forests. Simulation results show that firebreaks are effective in significantly reducing the area burned in different parts of the landscape. The performance of different strategies shows large variation. Although this has not been investigated further, such variation has likely been caused by topographic aspects and the positioning of firebreaks in the landscape in relation to climatic parameters. These results can therefore not be extrapolated beyond the simulated area, but do give an indication of the performance variation that may be expected when similar firebreaks are applied elsewhere. The results also show that model performance of all firebreak strategies is heavily and fairly consistently influenced by weather stream parameters. Sensitivity analyses of weather stream parameters show that although the reduction in total area burned varies, the ranking between strategies in their overall performance is consistent regardless of the weather pattern. Combined dry, warm and windy weather conditions lead to a 3.44-fold increase in total area burned as compared to the scenario with average weather conditions. In favourable weather conditions represented by wet, cold and nearly windless conditions, the model shows an 85% reduction in total burned area as compared to the average scenario. These results illustrate the significant impact of uncontrollable variables on the overall result.
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Books on the topic "Wildfire simulation"

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Pacific Northwest Research Station (Portland, Or.), ed. Evaluating soil risks associated with severe wildfire and ground-based logging. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2011.

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Smith, Eric L. A fire management simulation model using stochastic arrival times. Berkeley, Calif: U.S. Dept. of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station, 1987.

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Fight, Roger D. Users guide for FRCS: Fuel Reduction Cost Simulator software. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2006.

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H, Peterson Seth, ed. Using HFire for spatial modeling of fire in shrublands. Albany, CA: United States Dept. of Agriculture, Forest Service, Pacific Southwest Research Station, 2009.

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H, Peterson Seth, ed. Using HFire for spatial modeling of fire in shrublands. Albany, CA: United States Dept. of Agriculture, Forest Service, Pacific Southwest Research Station, 2009.

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Using HFire for spatial modeling of fire in shrublands. Albany, CA: United States Dept. of Agriculture, Forest Service, Pacific Southwest Research Station, 2009.

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E, Keane Robert, and Rocky Mountain Research Station--Ogden, eds. Development of input data layers for the FARSITE fire growth model for the Selway-Bitterroot Wilderness complex, USA. Ogden, UT (324 25th St., Ogden 84401): U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 1998.

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Bushfire survival situation: Leader's guide. Plymouth, MI: Human Synergistics International, 2005.

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Geospatial analysis and modeling. 2014.

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Book chapters on the topic "Wildfire simulation"

1

Petrasova, Anna, Brendan Harmon, Vaclav Petras, Payam Tabrizian, and Helena Mitasova. "Wildfire Spread Simulation." In Tangible Modeling with Open Source GIS, 155–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89303-7_12.

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Petrasova, Anna, Brendan Harmon, Vaclav Petras, and Helena Mitasova. "Wildfire Spread Simulation." In Tangible Modeling with Open Source GIS, 105–13. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25775-4_9.

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Hand, Michael S., Krista M. Gebert, Jingjing Liang, David E. Calkin, Matthew P. Thompson, and Mo Zhou. "Linking Suppression Expenditure Modeling with Large Wildfire Simulation Modeling." In Economics of Wildfire Management, 49–62. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0578-2_5.

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McKenzie, Donald, and Ajith H. Perera. "Modeling Wildfire Regimes in Forest Landscapes: Abstracting a Complex Reality." In Simulation Modeling of Forest Landscape Disturbances, 73–92. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19809-5_4.

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Mandel, Jan, Lynn S. Bennethum, Mingshi Chen, Janice L. Coen, Craig C. Douglas, Leopoldo P. Franca, Craig J. Johns, et al. "Towards a Dynamic Data Driven Application System for Wildfire Simulation." In Lecture Notes in Computer Science, 632–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11428848_82.

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Bessonov, Oleg, and Sofiane Meradji. "Efficient Parallel Solvers for the FireStar3D Wildfire Numerical Simulation Model." In Lecture Notes in Computer Science, 140–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25636-4_11.

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Avolio, Maria Vittoria, Salvatore Di Gregorio, Valeria Lupiano, and Giuseppe A. Trunfio. "Simulation of Wildfire Spread Using Cellular Automata with Randomized Local Sources." In Lecture Notes in Computer Science, 279–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33350-7_29.

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Ntinas, Vasileios G., Byron E. Moutafis, Giuseppe A. Trunfio, and Georgios Ch Sirakoulis. "GPU and FPGA Parallelization of Fuzzy Cellular Automata for the Simulation of Wildfire Spreading." In Parallel Processing and Applied Mathematics, 560–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32152-3_52.

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Asensio, M. I., L. Ferragut, D. Álvarez, P. Laiz, J. M. Cascón, D. Prieto, and G. Pagnini. "PhyFire: An Online GIS-Integrated Wildfire Spread Simulation Tool Based on a Semiphysical Model." In SEMA SIMAI Springer Series, 1–20. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61795-0_1.

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Yang, Jingmei, Huoping Chen, Salim Hariri, and Manish Parashar. "Self-optimization of Large Scale Wildfire Simulations." In Lecture Notes in Computer Science, 615–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11428831_76.

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Conference papers on the topic "Wildfire simulation"

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Grajdura, Sarah A., Sachraa G. Borjigin, and Deb A. Niemeier. "Agent-based wildfire evacuation with spatial simulation." In SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3423335.3428169.

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Davis, Ericson R., Christopher D. Johnson, David J. Levin, Rachel C. Morowitz, David K. Peterson, Michael R. Pouy, and Vitali Volovoi. "Aligning wildfire management resourcing decisions with operational needs." In 2014 Winter Simulation Conference - (WSC 2014). IEEE, 2014. http://dx.doi.org/10.1109/wsc.2014.7020002.

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"Geo-Referenced Image Data Assimilation For Wildfire Spread Simulation." In 2016 Spring Simulation Multi-Conference. Society for Modeling and Simulation International (SCS), 2016. http://dx.doi.org/10.22360/springsim.2016.anss.023.

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Gu, Feng, and Xiaolin Hu. "Towards applications of particle filters in wildfire spread simulation." In 2008 Winter Simulation Conference (WSC). IEEE, 2008. http://dx.doi.org/10.1109/wsc.2008.4736406.

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"Polynomial Chaos for sensitivity analysis in wildfire modelling." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.h10.hilton3.

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Yun, Shuai, Chongcheng Chen, Jianwei Li, and Liyu Tang. "Wildfire spread simulation and visualization in virtual environments." In 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM 2011). IEEE, 2011. http://dx.doi.org/10.1109/icsdm.2011.5969054.

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Rui Wu, Chao Chen, Sajjad Ahmad, John M. Volk, Cristina Luca, Frederick C. Harris, and Sergiu M. Dascalu. "A Real-time Web-based Wildfire Simulation System." In IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2016. http://dx.doi.org/10.1109/iecon.2016.7793478.

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Phan, Connie, and Hugh H. T. Liu. "A cooperative UAV/UGV platform for wildfire detection and fighting." In 2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing (ICSC). IEEE, 2008. http://dx.doi.org/10.1109/asc-icsc.2008.4675411.

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Yan, Xuefeng, Feng Gu, Xiaolin Hu, and Song Guo. "A dynamic data driven application system for wildfire spread simulation." In 2009 Winter Simulation Conference - (WSC 2009). IEEE, 2009. http://dx.doi.org/10.1109/wsc.2009.5429281.

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Jove, Jaume Figueras i., Antoni Guasch i. Petit, and Josep Casanovas-Garcia. "Simulation of Aerial Supression Tasks in Wildfire Events Integrated with Gisfire Simulator." In 2020 Winter Simulation Conference (WSC). IEEE, 2020. http://dx.doi.org/10.1109/wsc48552.2020.9383925.

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Reports on the topic "Wildfire simulation"

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Linn, R. R., and F. H. Harlow. Use of transport models for wildfire behavior simulations. Office of Scientific and Technical Information (OSTI), January 1998. http://dx.doi.org/10.2172/314172.

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Bradley, M. M., M. J. Leach, C. R. Molenkamp, C. H. Hall, L. Wilder, and L. A. Neher. Simulating Fine-Scale Atmospheric Processes: A New Core Capability and its Application to Predicting Wildfire Behavior. Office of Scientific and Technical Information (OSTI), February 2003. http://dx.doi.org/10.2172/15003838.

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