ESTIMATING ABOVE-GROUND BIOMASS IN ARAUCARIA ANGUSTIFOLIA AT TREE LEVEL USING AIRBORNE LIDAR DATA

This paper investigates the approach based on airborne
LiDAR for the quantification of Above-Ground Biomass
(AGB) of Araucaria angustifolia (Bertol.) Kuntze individuals
in a native forest fragment of the Atlantic Forest. A cloud of
ALS points was used, located in a fragment of native urban
forest in Curitiba-PR. The methodology consisted of:
classification of points, obtaining and smoothing the CHM,
peaks detection, and crown segmentation using eCognition
software. Mathematical models were adjusted to estimate the
AGB from the crown areas. Two equations were required in
order to estimate individual AGB. We found R2
(%) values
of 96.19 and 98.89 respectively. The total stock of AGB
found was 264.333 Kg. The LiDAR technology and the
methods applied here constitute non-destructive and accurate
tools for the quantification of biomass in native forests.