Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata

The popular simulation process that uses traditional cellular automata with a fixed time step to simulate forest fire spread may be limited in its ability to reflect the characteristics of actual fire development. This study combines cellular automata with an existing forest fire model to construct...

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Autores principales:	Liyang Sun, Congcong Xu, Yanglangxing He, Yanjun Zhao, Yuan Xu, Xiaoping Rui, Hanwei Xu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	forest fire spread simulation adaptive cellular automata remote sensing forest fire disaster Plant ecology QK900-989
Acceso en línea:	https://doaj.org/article/3d58cd7cb73144f7950c59994b0567b2
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spelling	oai:doaj.org-article:3d58cd7cb73144f7950c59994b0567b22021-11-25T17:37:08ZAdaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata10.3390/f121114311999-4907https://doaj.org/article/3d58cd7cb73144f7950c59994b0567b22021-10-01T00:00:00Zhttps://www.mdpi.com/1999-4907/12/11/1431https://doaj.org/toc/1999-4907The popular simulation process that uses traditional cellular automata with a fixed time step to simulate forest fire spread may be limited in its ability to reflect the characteristics of actual fire development. This study combines cellular automata with an existing forest fire model to construct an improved forest fire spread model, which calculates a speed change rate index based on the meteorological factors that affect the spread of forest fires and the actual environment of the current location of the spread. The proposed model can adaptively adjust the time step of cellular automata through the speed change rate index, simulating forest fire spread more in line with the actual fire development trends while ensuring accuracy. When used to analyze a forest fire that occurred in Mianning County, Liangshan Prefecture, Sichuan Province in 2020, our model exhibited simulation accuracy of 96.9%, and kappa coefficient of 0.6214. The simulated fire situation adapted well to the complex and dynamic fire environment, accurately depicting the detailed fire situation. The algorithm can be used to simulate and predict the spread of forest fires, ensuring the accuracy of spread simulation and helping decision makers formulate reasonable plans.Liyang SunCongcong XuYanglangxing HeYanjun ZhaoYuan XuXiaoping RuiHanwei XuMDPI AGarticleforest fire spread simulationadaptivecellular automataremote sensingforest fire disasterPlant ecologyQK900-989ENForests, Vol 12, Iss 1431, p 1431 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	forest fire spread simulation adaptive cellular automata remote sensing forest fire disaster Plant ecology QK900-989
spellingShingle	forest fire spread simulation adaptive cellular automata remote sensing forest fire disaster Plant ecology QK900-989 Liyang Sun Congcong Xu Yanglangxing He Yanjun Zhao Yuan Xu Xiaoping Rui Hanwei Xu Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
description	The popular simulation process that uses traditional cellular automata with a fixed time step to simulate forest fire spread may be limited in its ability to reflect the characteristics of actual fire development. This study combines cellular automata with an existing forest fire model to construct an improved forest fire spread model, which calculates a speed change rate index based on the meteorological factors that affect the spread of forest fires and the actual environment of the current location of the spread. The proposed model can adaptively adjust the time step of cellular automata through the speed change rate index, simulating forest fire spread more in line with the actual fire development trends while ensuring accuracy. When used to analyze a forest fire that occurred in Mianning County, Liangshan Prefecture, Sichuan Province in 2020, our model exhibited simulation accuracy of 96.9%, and kappa coefficient of 0.6214. The simulated fire situation adapted well to the complex and dynamic fire environment, accurately depicting the detailed fire situation. The algorithm can be used to simulate and predict the spread of forest fires, ensuring the accuracy of spread simulation and helping decision makers formulate reasonable plans.
format	article
author	Liyang Sun Congcong Xu Yanglangxing He Yanjun Zhao Yuan Xu Xiaoping Rui Hanwei Xu
author_facet	Liyang Sun Congcong Xu Yanglangxing He Yanjun Zhao Yuan Xu Xiaoping Rui Hanwei Xu
author_sort	Liyang Sun
title	Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
title_short	Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
title_full	Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
title_fullStr	Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
title_full_unstemmed	Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata
title_sort	adaptive forest fire spread simulation algorithm based on cellular automata
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3d58cd7cb73144f7950c59994b0567b2
work_keys_str_mv	AT liyangsun adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT congcongxu adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT yanglangxinghe adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT yanjunzhao adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT yuanxu adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT xiaopingrui adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata AT hanweixu adaptiveforestfirespreadsimulationalgorithmbasedoncellularautomata
_version_	1718412159990366208

Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata

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