Forest fire spreading geography cellular automaton simulation method

Abstract

The invention relates to a forest fire spreading geography cellular automaton simulation method. Through the method, a cellular space for operation of a model is established according to DEM data and tree variety flammability distribution data of a preset zone, a burning cellular stack and a high-risk cellular stack are respectively established; an igniting point is set, a cell where the igniting point is placed is added into the burning cellular stack; cells in the burning cellular stack are taken out in sequence, if the cells do not reach an extinguished state, a burning state is renewed, cells which are not ignited and are located on eight neighborhoods of the cells are added into the high-risk cellular stack; the cells are taken out from the high-risk cellular stack in sequence, when the igniting probability of the cells is larger than a preset threshold value, the state of the cells is renewed to a just-ignited state, and the cells are added into the burning cellular stack; and the above two steps are carried out repeatedly until the burning cellular stack is empty. The method can be used for analogue simulation of forest fire spreading with complex tree variety, and forest fire spreading results close to real situations are obtained.

Description

technical field [0001] The invention relates to a method for simulating the spreading trend of forest fires, in particular to a simulation method for geographical cellular automata of forest fires spreading. Background technique [0002] Forest fire is a common, very sudden and destructive natural disaster, which often brings serious threats and losses to forest resources, forest ecology and human life and property. Carrying out forest fire simulation to obtain the burning trend of forest fire is one of the effective means of fire prediction. It can assist fire prevention decision-making and reduce fire losses before forest fires burn in large areas. For nearly a century, human beings have been trying to use various methods to explore forest fire inducing factors, and consider using various effective observation methods to study forest fire combustion characteristics and spreading mechanisms, in order to obtain effective and reliable prediction methods to reduce losses in a ...

AI Technical Summary

Problems solved by technology

[0005] All kinds of CA forest fire models proposed at present mainly consider the ignited probability of the current cell from the flammability factor and distance coefficient of the cell tree species, without considering the burning intensity of combustibles (combustibles burn per unit area per unit time) The effect of different heat release) on the ignition probability of cells, and the current CA model building software lacks an application interface for interacting with GIS, cannot effectively process geographic data, and is difficult to implement. In terms of visualization of model simulation results, current research Two-dimensional representations are often used

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