A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

摘要: Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for inhibition spread wildland fires heterogeneous landscapes. This is two-level approach where dynamics fire are modeled as random Markov field process directed whose edge weights determined by Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, reduced to problem finding nodes (small land patches) favour propagation. Here, accomplished exploiting centrality statistics. We illustrate proposed through (a) an artificial forest randomly distributed density vegetation, (b) real-world case concerning island Rhodes in Greece major part its was burned 2008. Simulation results show outperforms benchmark/conventional policy reduction can be realized selective harvesting and/or prescribed burning based flammability vegetation. Interestingly, our reveals patches with sparse vegetation may act hubs fire.