02077nab a2200289 i 4500003000900000005001700009008004100026040001800067072000800085072000800093072000800101100002600109100002800135100003600163100002700199100003100226245009600257500009200353520097500445650002001420650002401440650002501464773019001489856008101679942000801760999001901768BR-BrBNA20260417121844.0260417b2019    bl.qr|pooa||| 00| 0 eng |  aBR-BrBNAbeng  aU40  aU10  aK10  aRex, Franciel Eduardo  aCorte, Ana Paula Dalla   aMachado, Sebastião do Amaral   aSilva, Carlos Alberto   aSanquetta, Carlos Roberto   aEstimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data  aPublicação on-line; Bibliography p. 9-11 (50 ref.); 1 table; 4 illus.; Summary (En)  a

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, Paraná 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.

Keywords: native forest, estimation equations, remote sensing.  aFLORESTA NATIVA  aMODELO MATEMÁTICO  aSENSORIAMENTO REMOTO0 029299347953dRio de Janeiro-RJ Instituto de Florestas - UFRRJ 1994o2025-0452tFloresta e Ambiente (Brazil)x1415-0980  /  ISSN 2179-8087 0nlinegv. 26(4) p. 1-11; (2019)wBR2026001242  uhttps://www.scielo.br/j/floram/a/v3jNTnsHy9JptVwfcgC3ZHj/?format=pdf&lang=en  cANA  c341452d341452