Estimating above-ground biomass of araucaria angustifolia (Bertol.) Kuntze using LiDAR Data

Abstract

The objective of this study was to test the performance of canopy data obtained from Airborne Laser Scanner (ALS) in generating estimates of above-ground biomass (AGB) of Araucaria angustifolia (Bertol.) Kuntze individuals. A cloud of ALS points located in a fragment of native urban forest in Curitiba, Parana was used. The procedures consisted of: classifying points; obtaining and smoothing the Canopy Height Model (CHM); detecting peaks and segmenting canopy using eCognition software. Mathematical models were adjusted to estimate the AGB from the crown areas. Two equations were required to estimate the individual AGB, while R2 (%) values of 96.19 and 98.89 were found. The total AGB stock found was 264.333 kg. The LiDAR technology and the methods for obtaining the information used in this work constitute non-destructive and precise tools for quantifying biomass in native forests.