Using Monte Carlo simulations to estimate relative fire ignition danger in a low-to-medium fire-prone region

A comprehensive assessment of fire ignition danger is nowadays a basic step towards the prioritization of fire management measures. In this study we propose performing a fire selectivity analysis using Monte Carlo simulations to statistically estimate the relative fire ignition danger in a low-to-intermediate fire-prone region such as Canton Ticino, Switzerland. We define fire ignition danger as the likelihood that at a given place a fire will be ignited. For each 25 m × 25 m pixel of the study area, landscape characteristics that may be related to the probability of fire ignition such as vegetation type, elevation, aspect, slope, urban–forest interface were first split into 9–12 categories. The selectivity of each category with respect to fire ignition was then statistically tested by means of Monte Carlo simulations. Finally, we proposed two different approaches for calculating the ignition danger index: cumulating the scores of the Monte Carlo simulations to a final index or producing synthetic scores by performing a principal component analysis of the Monte Carlo results. The validation of the resulting fire danger indices highlights the suitability of both proposed approaches. The PCA-option allows a slightly better discrimination between ignition and non-ignition points and may be of more general application.

Research highlights▶ A comprehensive assessment of fire ignition danger is nowadays a basic step towards the prioritization of fire management measures. ▶ In this study we propose performing a fire selectivity analysis using Monte Carlo simulations to statistically estimate the relative fire ignition danger in a low-to-intermediate fire-prone region such as Canton Ticino, Switzerland. ▶ We define fire ignition danger as the likelihood that at a given place a fire will be ignited. ▶ For each 25 m × 25 m pixel of the study area, landscape characteristics that may be related to the probability of fire ignition such as vegetation type, elevation, aspect, slope, urban–forest interface were first split into 9–12 categories. ▶ The selectivity of each category with respect to fire ignition was then statistically tested by means of Monte Carlo simulations. ▶ Finally, we proposed two different approaches for calculating the ignition danger index: cumulating the scores of the Monte Carlo simulations to a final index or producing synthetic scores by performing a principal component analysis of the Monte Carlo results. ▶ The validation of the resulting fire danger indices highlights the suitability of both proposed approaches. ▶ The PCA-option allows a slightly better discrimination between ignition and non-ignition points and may be of more general application.