Wildland fire spread modelling using cellular automata: evolution in large-scale spatially heterogeneous environments under fire suppression tactics
A. Alexandridis A , L. Russo B , D. Vakalis C , G. V. Bafas D and C. I. Siettos E F
+ Author Affiliations
- Author Affiliations
A Department of Electronics, Technological Educational Institute of Athens, Agiou Spiridonos, GR-12210, Aigaleo, Greece.
B Istituto di Ricerche sulla Combustione, Consiglio Nazionale delle Ricerche, Piazzale Tecchio 80, I-80125, Naples, Italy.
C Department of Forest Resources Development, Ministry of Rural Development and Food, GR-104 32, Athens, Greece.
D School of Chemical Engineering, National Technical University of Athens, GR-157 80, Athens, Greece.
E School of Applied Mathematics and Physical Sciences, National Technical University of Athens, GR-157 80, Athens, Greece.
F Corresponding author. Email: ksiet@mail.ntua.gr
International Journal of Wildland Fire 20(5) 633-647 https://doi.org/10.1071/WF09119
Submitted: 27 October 2009 Accepted: 9 November 2010 Published: 8 August 2011
Abstract
We show how microscopic modelling techniques such as Cellular Automata linked with detailed geographical information systems (GIS) and meteorological data can be used to efficiently predict the evolution of fire fronts on mountainous and heterogeneous wild forest landscapes. In particular, we present a lattice-based dynamic model that includes various factors, ranging from landscape and earth statistics, attributes of vegetation and wind field data to the humidity of the fuel and the spotting transfer mechanism. We also attempt to model specific fire suppression tactics based on air tanker attacks utilising technical specifications as well as operational capabilities of the aircrafts. We use the detailed model to approximate the dynamics of a large-scale fire that broke out in a region on the west flank of the Greek National Park of Parnitha Mountain in June of 2007. The comparison between the simulation and the actual results showed that the proposed model predicts the fire-spread characteristics in an adequate manner. Finally, we discuss how such a detailed model can be exploited in order to design and develop, in a systematic way, fire risk management policies.
Additional keywords: complex systems, geographical information systems, mountainous landscapes.
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