Detecting weak points of wildland fire spread: A cellular automata model risk assessment simulation approach

In this work, we propose a risk-assessment approach based on Cellular Automata (CA) simulations which incorporate both theoretical/ first principles and (semi)empirical fire behavioural models. The proposed approach can deal with spatial heterogeneity in both the fuel and landscape characteristics, can be coupled with Geographical Information Systems (GIS) and can take as input local meteorological data (even in real time). Using the CA model we are able to construct the topographic map of hazard intensity defined in terms of the expected burned area resulting from an ignition in a particular point of the region under surveillance. For our illustrations we used the case of Spetses Island whose a major part of its forest burned in 1990. Using the proposed framework, we revealed the weak points of fire spread risk, i.e. potential ignitions points which result to maximum likelihood of burned area.

In this work, we propose a risk-assessment approach based on Cellular Automata (CA) simulations which incorporate both theoretical/ first principles and (semi)empirical fire behavioural models. The proposed approach can deal with spatial heterogeneity in both the fuel and landscape characteristics, can be coupled with Geographical Information Systems (GIS) and can take as input local meteorological data (even in real time). Using the CA model we are able to construct the topographic map of hazard intensity defined in terms of the expected burned area resulting from an ignition in a particular point of the region under surveillance. For our illustrations we used the case of Spetses Island whose a major part of its forest burned in 1990. Using the proposed framework, we revealed the weak points of fire spread risk, i.e. potential ignitions points which result to maximum likelihood of burned area. © Copyright 2014, AIDIC Servizi S.r.l.