Abstract
Preharvest information on the quality of Scots pine (Pinus sylvestris) timber is required by the forest industry in Nordic countries, due to the strong association between the technical quality and product recovery of this species in particular. The objective of this study was to assess the accuracy of estimating external quality attributes and classifying the quality of mature Scots pine trees by terrestrial laser scanning (TLS). The tree quality was estimated using a random forest approach, based on both field and TLS measurements of stem diameters, tree height and branch heights. The relative root mean squared errors of the TLS measurements for tree height, diameter, diameter at 6 m and the lowest living and dead branch height were 7.1%, 5.9%, 8.9%, 9.6% and 42.9%, respectively. The highest errors of the branch heights were caused by the shadowing effect in the point cloud data. The quality classes were estimated accurately, based on both (field and TLS measured) tree attributes. Trees were classified with 95.0% and 83.6% accuracy into three operationally-important quality classes and with 87.1% and 76.4% accuracy into five classes using, field or TLS measurements, respectively. The obtained quality classification results were promising. The enhanced tree quality information could have a significant effect on planning forest management procedures, wood supply chains and optimizing the flow of raw materials. To fully integrate tree quality measurements in operational forestry, the methods used should be fully automated.
Highlights
Information on the quality of available timber is an essential input for wood procurement planning, because the technical quality of standing timber directly affects the production potential and its value in the forest industry [1]
terrestrial laser scanning (TLS) measurements offer a new approach to derive precise information on standing trees, which can be utilized in forestry application and forest management procedures
Tree quality attributes can be measured in addition to traditionally measured parameters accurately from dense 3D point clouds
Summary
Information on the quality of available timber is an essential input for wood procurement planning, because the technical quality of standing timber directly affects the production potential and its value in the forest industry [1]. The most influential quality factors are the stem form, the heights of the lowest living (lb) and dead branches (db) and the branch size distribution (diameter, location and number of branches) (e.g., [2,3]), of which the branch size distribution has the most pronounced effect on timber quality [4]. Bucking of the tree stems is affected by the lengths of the branchless trunk section, dead branch section and living crown. The information available does not fully support demand-based wood procurement
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