Predicting wood quantity and quality attributes of balsam fir and black spruce using airborne laser scanner data

The objective of this study was to determine whether a suite of wood quantity and quality attributes of balsam fir and black spruce forests could be predicted using airborne laser scanner data. In situ estimates of stand structure and wood fibre attributes were derived from measurements at sample pl...

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Bibliographic Details
Published in:Forestry
Main Authors: Luther, Joan E., Skinner, Randy, Fournier, Richard A., van Lier, Olivier R., Bowers, Wade W., Coté, Jean-François, Hopkinson, Chris, Moulton, Tim
Format: Text
Language:English
Published: Oxford University Press 2013
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Online Access:http://forestry.oxfordjournals.org/cgi/content/short/cpt039v1
https://doi.org/10.1093/forestry/cpt039
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Summary:The objective of this study was to determine whether a suite of wood quantity and quality attributes of balsam fir and black spruce forests could be predicted using airborne laser scanner data. In situ estimates of stand structure and wood fibre attributes were derived from measurements at sample plots covering a wide range of forest conditions of insular Newfoundland. Models developed to predict field estimates explained 52–90 per cent of the variation in structure attributes, including mean and quadratic mean diameter at breast height, average and dominant height, stem density, basal area, total and merchantable volume and above-ground total biomass. Cross-validated root mean square errors were <24 per cent of mean values, with the exception of stem density, for which errors were 27–32 per cent. Models of fibre attributes explained 18–53 per cent of the variation in fibre length, wood density, radial diameter, coarseness, microfibril angle, modulus of elasticity, wall thickness and specific surface with cross-validated root mean square errors of <14 per cent of mean values. Similar results were achieved for fibre attribute models derived using geographic, climate and vegetation variables. The results demonstrate potential for inventory of quantity and quality attributes over a large region of boreal forests in Newfoundland, Canada.