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Forests 2014, 5(8), 1879-1895; doi:10.3390/f5081879

Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning

1
Department of Forest Sciences, University of Helsinki, FI-00014 Helsinki, Finland
2
Centre of Excellence in Laser Scanning Research, Finnish Geodetic Institute, FI-02431 Masala, Finland
3
School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland
4
Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, FI-02431 Masala, Finland
5
Department of Real Estate, Planning and Geoinformatics, Aalto University, FI-00076 Aalto, Finland
6
Civil Engineering and Building Services, Helsinki Metropolia, University of Applied Sciences, FI-00079 Helsinki, Finland
7
Department of Geography and Geology, University of Turku, FI-20014 Turku, Finland
*
Author to whom correspondence should be addressed.
Received: 3 March 2014 / Revised: 1 July 2014 / Accepted: 23 July 2014 / Published: 31 July 2014
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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. View Full-Text
Keywords: remote sensing; forest inventory; GIS; forest management planning; laser scanning; terrestrial laser scanning; timber quality; forest technology remote sensing; forest inventory; GIS; forest management planning; laser scanning; terrestrial laser scanning; timber quality; forest technology
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MDPI and ACS Style

Kankare, V.; Joensuu, M.; Vauhkonen, J.; Holopainen, M.; Tanhuanpää, T.; Vastaranta, M.; Hyyppä, J.; Hyyppä, H.; Alho, P.; Rikala, J.; Sipi, M. Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning. Forests 2014, 5, 1879-1895.

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