Abstract
Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a 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 network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network 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 major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.
Highlights
Efficient wildland fire control is one of the most challenging and important problems in ecology [1]
Having computed the adjacency matrix, centrality statistics such as the Betweenness Centrality (BC) [37] and the Bonacich information criterion [36] can be used for the identification of nodes that contribute more to the fire spread through the network
The shaded area shows the range of fire breaks densities where differences between the Bonacich and the BC-based are statistically significant from the random-based distribution
Summary
Efficient wildland fire control is one of the most challenging and important problems in ecology [1]. Fire is an essential renewing contributor of the ecological cycle. Fuel management treatments have been extensively applied at the local scale, but they have had a limited influence on the evolution of wildfires at the landscape scale [2, 3]. At this scale level, experimental work is prohibitory, and the majority of previous studies on the spatial distribution of fuel management activities have been theoretical [2]. Observations on real wildland fire cases have evidenced that fire size and severity can be mitigated by proper
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