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Scientia Silvae Sinicae ›› 2024, Vol. 60 ›› Issue (4): 52-61.doi: 10.11707/j.1001-7488.LYKX20220863

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Simulation of Forest Fire Spread and Optimization of Forest Fire Emergency Prevention Planning

Zhuo Chen1,Haiyang Liu1,*,Quanyi Huang1,Mingzhang Zheng2,Jian Li1   

  1. 1. Institute for Public Safety Research, Tsinghua University Beijing 100084
    2. Jilin Province Forestry Surveydesign & Research Institute Changchun 130022
  • Received:2022-12-06 Online:2024-04-25 Published:2024-05-23
  • Contact: Haiyang Liu

Abstract:

Objective: In this study, cloud computing method was used to simulate the spread process of forest fire and plan the fire emergency path, so as to promote the rescue forces to quickly and efficiently reach the designated place, and to reserve enough time for arranging forest fire prevention measures. This study also puts forward constructive suggestions for forest fire emergency response and prevention planning in Dongchang District, Tonghua City, Jilin Province. Methods: An on-site investigation was conducted in Dongchang District, Tonghua City, Jilin Province, and then the model deduction was carried out. With a view to the differences between single-source and multi-source forest fires, the emergency path planning model and Dijkstra algorithm were used to simulate and calculate the shortest rescue path in the case of single-source forest fires, and the multi-source forest fire priority theory was incorporated to maximize the utilization of rescue resources. The FARSITE model was used to simulate the spread rate of forest fires in regional examples, and real-time data of each stage after forest fires occurrence were obtained. In considering the resource layout near forest fires and road traffic capacity comprehensively, the rescue path was calculated and the fire prevention road layout was carried out, to verify the feasibility of the method, and the rescue path of forest fires emergency response was intelligently optimized. Result: Based on the formula of a single fire point in a general forest fire occurrence, the priority theory was introduced for two or more fire points, and then Dijkstra algorithm was used to deduce in turn according to the severity of the fire. In addition, μ, as a capacity coefficient, was added to consider the influence of road conditions and road attributes on the rescue transit time, and obtain a new path formula. By using the FARSITE model, the spread rate of the "5.3" general forest fire (20100503-220502-01) in 2010 was simulated. In five hours after the fire started, if there was no effective human intervention, the fire would turn into a major forest fire and spread to the residential areas. Due to the influence of wind direction, the fire priority on the northeast of the fire source would be higher than that on the north. If there are conditions for simultaneous rescue, the emergency resources should be tilted according to the priority. Conclusion: The simulation results show that by using the emergency path planning model, Dijkstra algorithm and priority theory, the acquisition rate of rescue paths can be improved, and resources and personnel can be allocated in advance. FARSITE simulation combined with fire road planning can effectively improve the efficiency of forest fire decision-making, and form a forest fire emergency response and prevention planning scheme with half the effort.

Key words: intelligent forestry, emergency planning, forest fire decision-making, cloud computing, FARSITE, Dijkstra

CLC Number: