控制荒地火灾的异质森林景观中防火带空间分布的复杂网络理论方法
A complex network theory approach for the spatial distribution of fire breaks in heterogeneous forest landscapes for the control of wildland fires
摘要：
基于复杂网络理论，我们提出了一种计算方法，解决燃料中断的空间分布的抑制蔓延和规模的荒地火灾异质景观。这是一个两轮的方法，其中火灾蔓延的动态被建模为一个随机马尔可夫场过程的有向网络，其边的权重，提供了一个国家的最先进的元胞自动机模型，集成了详细的地理信息系统，景观和气象数据。在此框架内，燃料中断的空间分布被减少到寻找网络节点之间的火灾蔓延速度更快，因此他们的去除有利于抑制火灾蔓延的问题。在这里，这是利用信息中心统计完成的。我们说明了所提出的方法，通过（a）随机分布的植被密度的人工森林，和（b）一个真实世界的情况下，在希腊的罗得岛，其森林的主要部分在2008年烧毁。仿真结果表明，该方法明显优于随机分布的燃料中断的基准策略。
英文摘要：
Based on complex network theory, we propose a computational methodology that addresses the spatial distribution of fuel breaks for the inhibition of the spread and size of wildland fires on heterogeneous landscapes. This is a two-tire approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights, are provided by a state-of-the-art cellular automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding the network nodes among which the fire spreads faster, thus their removal favours the inhibition of the fire propagation. Here this is accomplished exploiting the information centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose a major part of its forest burned in 2008. Simulation results show that the methodology outperforms significantly the benchmark tactic of random distribution of fuel breaks.
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