Abstract
The objective of this work was to obtain the stem volume from 3D-cloud points generated by terrestrial laser scanning in Eucalyptus stands. The processing started with using algorithms for tree detection in plantation (TDP) and stem filtering (Filter Dmax). Then, the acquisition of the total height was made semi-automatically and tridimensional modelling was performed through the adjustment of circumferences (AC) and the so-called triangulated irregular network (TIN). The results were compared with field data and conventional stem volume measurements. The detection accuracy was 100% for the trees in the plots while filtering reached 70% of the stem surface. The total height presented R2 = 0.98 and residuals less than 5%. The estimated volumes, analyzed in sections with a length of 2 m, were in average smaller than that obtained by the conventional Smalian method. The occlusion of points in the tree crown precluded obtaining the total stem volume.
Highlights
AND OBJECTIVESNon-destructive methods of tree scaling constitute a relevant advance for forest measurements
The present study introduces an evaluation of the automation for 3D reconstruction of logs and the calculation of volume from terrestrial laser scanning in clonal plantations of Eucalyptus urograndis
The use of terrestrial laser scanning for trunk modelling represents an advance in data collection as it is an alternative to destructive tree scaling methods
Summary
Non-destructive methods of tree scaling constitute a relevant advance for forest measurements. They enable the obtention of stem volumes without felling the trees by using optical instruments, which facilitate faster data collection and reduction of field work (Kankare et al, 2013; Nicoletti et al, 2012). The Terrestrial Laser Scanning (TLS) provides high precision measurements through a dense three-dimensional (3D) point cloud (Silva et al, 2013). This technology has been tested to collect data in forest stands by means of single scanning (a laser station) or multiple scanning (two or more stations). The geometric shapes provided by the points in the scan are important so that algorithms can be developed to indicate whether a certain set of points belongs to the tree stem, to the branches, to the leaves, or to another object in the field of view of the equipment
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