Forest fire spread prediction based on improved Wang Zhengfei model combined with cellular automata
[Objective]At present,the prediction of forest fire spread in our country still has problems such as low prediction accuracy and poor universality.In response to these problems,this study improved the forest fire spread prediction model based on Wang Zhengfei velocity model combined with multidimensional cellular automata,the effectiveness of the model under different regions and resolutions was studied,which enhanced the adaptability of the model to data of different resolutions,so as to better predict the spread of forest fires,and provided a scientific and reasonable technical means for the prediction and management of forest fire spread.[Method]Using the forest fires that occurred on October 28,2011 in the Greater Khingan Mountains of Heilongjiang province(resolution 500 m)and the forest fires that occurred in the Liangshan area of Sichuan province on March 29,2022(resolution 30 m)as data sources,the fires were extracted happening time and the front line of the spreading process.Introducing the normalized difference vegetation index(NDVI)to improve Wang Zhengfei model,and using the deconvolution algorithm to improve the cellular automata algorithm,then comparing the accuracy of the output results of the improved model and the model accuracy performance.[Result]The accuracy of the improved model has been significantly improved.Among them,the kappa coefficient of the improved model in the Greater Khingan Mountains experiment in Heilongjiang province had increased by 0.029 7,and the area error rate had decreased by 21.33%,the first fire site is predicted to have 170 fire points,and the average fire speed is 0.75 m/min.In Muli county,Sichuan province,the kappa coefficient of the improved model increased by 0.116 5,and the area error rate decreased by 37.08%,the second fire site is predicted to have 1 795 fire points,and the average fire speed is 4.00 m/min.[Conclusion]The improved forest fire spread prediction model can predict the fire spread more effectively and calculate the location of the most likely fire point,and its prediction results are highly consistent and accurate,which improves the practicability of forest fire spread simulation prediction.Compared with the original model,the improved model can improve the prediction accuracy under different resolution data,and can provide scientific basis for forest fire prevention and management.
forest fire spreadmodel improvementWang Zhengfei modelcellular automataforest management
NETL
NSTL
万方数据
