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针对传统林火蔓延仿真模型在模拟大范围森林火灾时误差大和效率低的问题,对文献[10]的林火模型添加时间修正来提升林火蔓延模拟的准确性,提出耦合地理元胞自动机模拟林火蔓延过程的仿真算法。分析了元胞自动机时间步长对模拟精度的影响,优化时间步长选择,提高了模拟大规模森林火灾的精度及效率。以模拟2006年5月大兴安岭林区森林大火蔓延过程为例验证本算法,发现地理元胞自动机算法中时间步长取整个元胞完全燃烧所需时间的1/8效果最好,林火蔓延模拟结果与实际TM影像解译的火情时空一致性较高,Kappa系数平均为0.6352,准确率平均为87.89%。算法可用于实际林火蔓延过程的重现及趋势预测,且算法可逆。
Aiming at the problem of large error and large inefficiency in simulating forest fires, aiming at the problem of simulating the fire spread of traditional forest fires, the paper adds the time correction to the forest fire model in [10] to improve the accuracy of the simulation of forest fire spread. A coupled geocellular automaton Simulation Algorithm for Simulating Forest Fire Spread Process. The influence of time step of cellular automaton on simulation precision is analyzed, and the choice of time step is optimized to improve the precision and efficiency of simulating large-scale forest fire. The simulation of the forest fire in Daxinganling forest area in May 2006 was used as an example to verify the algorithm. It was found that the time-step of the Cellular Automata algorithm took 1/8 of the time required for the complete combustion of the entire cell, and the fire spread The consistency of fire time-space between the simulation results and the actual TM image interpretation is high, with an average Kappa coefficient of 0.6352 and an average accuracy rate of 87.89%. The algorithm can be used to predict the actual forest fire spread and forecast the trend, and the algorithm is reversible.