Enhancing the Realism of Wildfire Simulation Using Composite Bézier Curves

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Resumen

One of the consequences of climate change is the increase in forest fires around the world. In order to act quickly when this type of natural disaster occurs, it is important to have simulation tools that allow a better approximation of the evolution of the fire, especially in Wildland Urban Interface (WUI) areas. Most forest fire propagation simulators tend to represent the perimeter of the fire in a polygonal way, which often does not allow us to capture the real evolution of the fire in complex environments, both at the terrain and vegetation levels. In this work, we focus on Elliptical Wave Propagation (EWP) based simulators, which represent the perimeter of the fire with a set of points connected to each other by straight lines. When the perimeter grows and new points must be added, the interpolation method used is linear interpolation. This system generates unrealistic shapes of fires. In this work, an interpolation method leveraging Composite Bézier Curves (CBC) is proposed to generate fire evolution shapes in a more realistic way. The proposed method has been incorporated into FARSITE, a well-known EWP-based forest fire spread simulator. Both interpolation methods have been applied to ideal scenarios and a real case. The results show that the proposed interpolation method (CBC) is capable of generating more realistic fire shapes and, in addition, enables the simulator the ability to better simulate the spread of fire in WUI zones.
Idioma originalInglés
Título de la publicación alojadaComputational Science – ICCS 2024 - 24th International Conference, 2024, Proceedings
EditoresLeonardo Franco, Clélia de Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M. A. Sloot
Páginas151-165
Número de páginas15
Volumen14832
ISBN (versión digital)978-3-031-63749-0
DOI
EstadoPublicada - 2024

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen14832 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

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