Canadian Forest Service Publications

Predicting wood fiber attributes using local-scale metrics from terrestrial LiDAR data: a case study of Newfoundland conifer species. 2015. Blanchette, D.; Fournier, R.A.; Luther, J.E.; Côté, J.-F. Forest Ecology and Management 347: 116-129.

Year: 2015

Available from: Atlantic Forestry Centre

Catalog ID: 36307

Language: English

CFS Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.106/j.foreco.2015.03.013

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Abstract

Knowledge of wood fiber attributes (WFA) is important for evaluating forest resources and optimizing efficiency in the forest industry. To improve our ability to estimate WFA in the forest, we analyzed the relationships between structural metrics derived from terrestrial laser scanner (TLS) data and four key attributes of industrial significance: wood density, fiber length, microfibril angle, and coarseness. We developed a suite of structural metrics that relate to four aspects of the forest: canopy structure, competition, vegetation density, and local topography. We modeled FA for sites dominated by black spruce (Picea mariana) and balsam fir (Abies balsamea) trees. For black spruce sites, R2 values ranged from 63% to 72%. Structural metrics that relate to competition were the strongest explanatory variables. For balsam fir sites, R2 ranged from 37% to 63% using structural metrics that relate mostly to canopy structure. Our results demonstrate that local structural variables are useful explanatory variables for predicting WFA of the dominant coniferous species in Newfoundland.

Plain Language Summary

Knowledge of wood fiber attributes is needed to better evaluate forest resources, maximize benefits and increase forest sector competitiveness. This paper assesses the capability to predict wood fiber attributes of balsam fir and black spruce forests using terrestrial laser scanning (TLS) data. The paper describes the development of forest structural metrics that characterize canopy structure, competition, vegetation density and local topography and the use of these metrics to estimate industrially significant attributes – wood density, fiber length, microfibril angle and coarseness. The results demonstrate that local structural metrics are useful explanatory variables for predicting wood fiber attributes of the dominant coniferous species of Newfoundland.

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