Representation and evaluation of wildfire propagation simulations

Filippi, Jean Baptiste; Mallet, Vivien; Nader, Bahaa

doi:10.1071/wf12202

Cited by 55 publications

(53 citation statements)

References 18 publications

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“…Our evaluation relies on scoring methods that were analysed (and, for two of them, proposed) in Filippi et al (2013). We denote S(t) as the burned surfaces at time t in the simulation.…”

Section: Comparison Scoresmentioning

confidence: 99%

“…The first step in evaluating model performance is to be able to evaluate single simulation results against observations. Such scoring methods have been the subject of several studies, initiated by Fujioka (2002) and recently compiled and extended in Filippi et al (2013). Basically, it is clear from all these studies that a single value cannot be representative of a model performance, as it only gives limited insights on all aspects of performance, while the analysis of a human eye provides a better understanding of what was good and what went wrong.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of forest fire models on a large observation database

Filippi

Mallet

Nader

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and approximative ignition point). Simulations for all cases are carried out with four different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations run as first guesses with no tuning for any of the models or cases. This approach leads to a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Disregarding the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical ones. Data and source codes used for this paper are freely available to the community.

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“…Our evaluation relies on scoring methods that were analysed (and, for two of them, proposed) in Filippi et al (2013). We denote S(t) as the burned surfaces at time t in the simulation.…”

Section: Comparison Scoresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of forest fire models on a large observation database

Filippi

Mallet

Nader

2014

Nat. Hazards Earth Syst. Sci.

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“…Several previous studies have sought to validate fire spread simulation systems by comparing simulated fire spread against historical fire data, for example the studies of Finney (Finney 2000), Fujioka (Fujioka 2002), Arca et al (Arca et al 2007), and Fillipi et al (Filippi et al 2014). In common with previous validation exercises, this study found that that the ability to perform validation was limited by the reliability of available data, with fireground weather presenting the largest obstacle.…”

Section: Discussionmentioning

confidence: 82%

Evaluating wildfire simulators using historical fire data

Milne¹,

Kelso²,

Murphy

et al. 2014

Advances in Forest Fire Research

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A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos.Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da instituição detentora da supramencionada licença.Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra. Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso.Evaluating wildfire simulators using historical fire data Autor(es):Milne, George J; Kelso, Joel K; Mellor, Drew; Murphy, Mary E AbstractHigh-performance wildfire simulators allow the future location of a wildfire to be rapidly predicted. The accuracy of such simulators needs to be evaluated; this can be achieved by comparing simulated and observed spread for documented historical fires. A key issue relates to the accuracy of data obtained from historical fires, such as the time-varying fire location, fire-ground weather and accuracy of fuel type, load and structure data. A methodology used to evaluate the accuracy of wildfire simulators using historical fire data is presented and applied to the AUSTRALIS wildfire simulator using the four distinct phases of a large-scale wildfire occurring in Western Australian sand-plain heathlands and a fire reconstruction report on this fire produced by a wildfire expert. Challenges encountered in performing this validation exercise are highlighted.

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“…We test it by assimilating airborne infrared images captured from two large-scale experiments conducted in South Australia and assess the forecast reliability by means of Jaccard (Jaccard 1901;Filippi et al 2014c) and Sørensen (Sørensen 1948;Perry et al 1999) similarity indices, finding great agreement in the available short-term forecast.…”

Section: Introductionmentioning

confidence: 99%

Short-term fire front spread prediction using inverse modelling and airborne infrared images

Rios

Pastor

Valero

et al. 2016

Int. J. Wildland Fire

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Abstract.A wildfire forecasting tool capable of estimating the fire perimeter position sufficiently in advance of the actual fire arrival will assist firefighting operations and optimise available resources. However, owing to limited knowledge of fire event characteristics (e.g. fuel distribution and characteristics, weather variability) and the short time available to deliver a forecast, most of the current models only provide a rough approximation of the forthcoming fire positions and dynamics. The problem can be tackled by coupling data assimilation and inverse modelling techniques. We present an inverse modelling-based algorithm that uses infrared airborne images to forecast short-term wildfire dynamics with a positive lead time. The algorithm is applied to two real-scale mallee-heath shrubland fire experiments, of 9 and 25 ha, successfully forecasting the fire perimeter shape and position in the short term. Forecast dependency on the assimilation windows is explored to prepare the system to meet real scenario constraints. It is envisaged the system will be applied at larger time and space scales.

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Representation and evaluation of wildfire propagation simulations

Cited by 55 publications

References 18 publications

Evaluation of forest fire models on a large observation database

Evaluation of forest fire models on a large observation database

Evaluating wildfire simulators using historical fire data

Short-term fire front spread prediction using inverse modelling and airborne infrared images

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