4.7 Article

Parameter estimation of fire propagation models using level set methods

Journal

APPLIED MATHEMATICAL MODELLING
Volume 92, Issue -, Pages 731-747

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2020.11.030

Keywords

Wildland fire propagation model; Level set methods; Parameter estimation; Optimization

Funding

  1. Air Force Office of Scientific Research [FA9550-15-1-0530]

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This study proposes an approach to estimate the parameters of a wildland fire propagation model by combining an empirical rate of spread and level set methods to minimize the symmetric difference between predicted and measured fire fronts. Results show the effectiveness of this method in two simulated scenarios and a case study based on data from the 2002 Troy fire in Southern California, both qualitatively and quantitatively.
The availability of wildland fire propagation models with parameters estimated in an accurate way starting from measurements of fire fronts is crucial to predict the evolution of fire and allocate resources for firefighting. Thus, we propose an approach to estimate the parameters of a wildland fire propagation model combining an empirical rate of spread and level set methods to describe the evolution of the fire front over time and space. The estimation of parameters affecting the rate of spread is performed by using fire front shapes measured at different time instants as well as wind velocity and direction, landscape elevation, and vegetation distribution. Parameter estimation is done by solving an optimization problem, where the objective function to be minimized is the symmetric difference between predicted and measured fronts at different time instants. Numerical results obtained by the application of the proposed method are reported in two simulated scenarios and in a case study based on data originated by the 2002 Troy fire in Southern California. The obtained results showcase the effectiveness of the proposed approach both from qualitative and quantitative viewpoints. (c) 2020 Elsevier Inc. All rights reserved.

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