A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Assessing log geometry and wood quality in standing timber using terrestrial laser-scanning point clouds




TekijätPyörälä, Jiri; Kankare, Ville; Liang, Xinlian; Saarinen, Ninni; Rikala, Juha; Kivinen, Veli-Pekka; Sipi, Marketta; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko

KustantajaOXFORD UNIV PRESS

KustannuspaikkaOXFORD

Julkaisuvuosi2019

JournalForestry

Tietokannassa oleva lehden nimiFORESTRY

Lehden akronyymiFORESTRY

Vuosikerta92

Numero2

Aloitussivu177

Lopetussivu187

Sivujen määrä11

ISSN0015-752X

eISSN1464-3626

DOIhttps://doi.org/10.1093/forestry/cpy044


Tiivistelmä
Wood procurement in sawmills could be improved by resolving detailed three-dimensional stem geometry references from standing timber. This could be achieved, using the increasingly available terrestrial point clouds from various sources. Here, we collected terrestrial laser-scanning (TLS) data from 52 Scots pines (Pinus sylvestris L.) with the purpose of evaluating the accuracy of the log geometry and analysing its relationship with wood quality. For reference, the log-specific top-end diameter, volume, tapering, sweep, basic density and knottiness were measured in a sawmill. We produced stem models from the TLS data and bucked them into logs similar to those measured in the sawmill. In comparison to the sawmill data, the log-specific TLS-based top-end diameter, volume, taper and sweep estimates showed relative mean differences of 1.6, -2.4, -3.0 and 78 per cent, respectively. The correlation coefficients between increasing taper and decreasing wood density and whorl-to-whorl distances were 0.49 and -0.51, respectively. Although the stem-model geometry was resolved from the point clouds with similar accuracy to that at the sawmills, the remaining uncertainty in defining the sweep and linking the wood quality with stem geometry may currently limit the method's feasibilities. Instead of static TLS, mobile platforms would likely be more suitable for operational point cloud data acquisition.



Last updated on 2025-27-01 at 19:14