Differences in Canopy Cover Estimations from ALS Data and Their Effect on Fire Prediction

Abstract

Canopy cover is a primary attribute used in empirical wildfire models for certain fuel types. Accurate estimation of canopy cover is a key to ensuring accurate prediction of fire spread and behaviour in these fuels. Airborne Laser Scanning (ALS) is a promising active remote sensing technology for estimating canopy cover in natural ecosystems since it can penetrate and measure the vegetation canopy. Various methods have been developed to estimate canopy cover from ALS data. However, little attention has been given to the evaluation of algorithms used to calculate canopy cover and the subsequent influence these algorithms can have on wildfire behaviour models.