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Study on Forest Fire spread Model of Multi-dimensional Cellular Automata based on Rothermel Speed Formula

ABSTRACT

Background:

The spread of forest fire is a complex natural phenomenon. The cellular automata(CA) is a common model of forest fire spread, which fails to combine the unique combustion properties of forest fire spreading, resulting in inaccurate simulation results. In order to improve the accuracy of forest fire spread simulation, the Rothermel forest fire rate formula is simplified and combined with CA to form a multi-dimensional cellular automata(MD-CA) model of forest fire spread with different combustion properties in each cell. The formulas of the spread rate of forest fire in eight directions are obtained through the training datasets, and the testing datasets are used to compare the simulation results of CA model, MD-CA model and the actual fire spread.

Results:

It is concluded that the simulated areas and perimeters of the MD-CA are closer to the actual forest fire spread, the area error rate is 9.42% - 15.63%, and the perimeter error is 4.21% - 8.99%, The errors are less than CA model.

Conclusion:

The MD-CA model based on Rothermel has the strong ability to simulate the spread of fire in the laboratory, however, how to eliminate the errors over time is the task of the next stage.

Keywords:
Rothermel; cellular automata; forest fire spread; fire contour area and perimeter; error rate

HIGHLIGHTS

The complex Rothermel formula is simplified to better adapt to cellular automata.

The forest fire spread model of multi-dimensional cellular automata combines slope, moisture content, wind speed and other factors.

Multi-dimensional cellular automata has a better effect of spreading simulation.

It provides a new method for the development of forest fire spread model.

UFLA - Universidade Federal de Lavras Universidade Federal de Lavras - Departamento de Ciências Florestais - Cx. P. 3037, 37200-000 Lavras - MG Brasil, Tel.: (55 35) 3829-1706, Fax: (55 35) 3829-1411 - Lavras - MG - Brazil
E-mail: cerne@dcf.ufla.br