Applications of Airborne Laser Scanning in Forest Fuel Assessment and Fire Prevention

Forest fire management requires accurate, spatially explicit and up-to date information on forest fuels and their vertical structure. Airborne laser scanning (ALS) provides 3-D vegetation models to map accurate fuel properties critical for modelling fire behaviour. Laser point cloud data stratified into height intervals coupled with spectral information can provide accurate fuel type maps, especially if non-parametric classifiers are used. Canopy bulk density (CBD) depends on ALS metrics related to canopy volume and biomass to yield regression models ranging between 0.77 and 0.94 in R2. ALS estimates canopy base height (CBH) after the identification of the gap in the canopy that describes the beginning of the tree crown. Due to laser point density among other factors, CBH for individual trees is usually less accurate than for plots. Penetration through the upper canopy and the low height of the surface fuels combined with a low laser pulse density constrain the estimation of surface canopy height (SCH). ALS together with optical sensors map the above mentioned fuels properties more accurately than with any of these sensors alone due to the synergy of the structural and spectral information collected by each sensor. Despite the fact that most attempts at using ALS for fire management have been focused on characterization of fuels at the pre-fire stage or during the fire, multi-temporal ALS data also have high potential at the post-fire stage to estimate burn severity and vegetation regeneration after fire.