Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements

The present study sets a methodological framework to combine LiDAR derived data with fire behaviour models in order to assess fire risk at landscape level for forest management and planning. Two forest areas of the Model Forest in Urbión, Soria (Central Spain) were analyzed, covering 992.7 ha and 221.7 ha. The modelling phase was based in 160 field sample plots as ground data, and the LiDAR data had a density of first returns of 2 pulses/m2, which were used to construct 13 models for stand variables (e.g. basal area, stem volume, branch biomass). The coefficients of determination ranged from 0.167 for shrub cover, to 0.906 for dominant height. The modelled variables were used for a classification of fuel types compatible with the continuous data. The simulation phase was performed using the spatialized data on FlamMap in order to assess the potential fire behaviour resulting across the whole landscape for four scenarios of moisture and wind conditions. The results showed maps of fire intensity and probability of fire occurrence, based on the simulation of 500 random ignition points, which allowed the analysis of the spatial relation between the initial state and allocation of forest resources and their risk of fire. The methodology proposed, as well as the results of this research are directly applicable for operational forest planning at landscape level.

► Fire behaviour and occurrence are estimated with defined scenarios in a forest area.
► We present a methodology that combines forest fire simulators and LiDAR data.
► It provides 13 models for stand level variables and its spatialization.
► A set of rules to classify fuel types compatible with the continuous data is presented.
► The methodology IS applicable for operational planning purposes at landscape level.