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

被引:40
作者
Kankare, Ville [1 ,2 ]
Joensuu, Marianna [1 ]
Vauhkonen, Jari [1 ,2 ,3 ]
Holopainen, Markus [1 ,2 ]
Tanhuanpaa, Topi [1 ,2 ]
Vastaranta, Mikko [1 ,2 ]
Hyyppa, Juha [2 ,4 ]
Hyyppa, Hannu [2 ,5 ,6 ,7 ]
Alho, Petteri [2 ,5 ,8 ]
Rikala, Juha [1 ]
Sipi, Marketta [1 ]
机构
[1] Univ Helsinki, Dept Forest Sci, FI-00014 Helsinki, Finland
[2] Finnish Geodet Inst, Ctr Excellence Laser Scanning Res, FI-02431 Masala, Finland
[3] Univ Eastern Finland, Sch Forest Sci, FI-80101 Joensuu, Finland
[4] Finnish Geodet Inst, Dept Remote Sensing & Photogrammetry, FI-02431 Masala, Finland
[5] Aalto Univ, Dept Real Estate Planning & Geoinformat, FI-00076 Aalto, Finland
[6] Univ Appl Sci, Helsinki Metropolia, Civil Engn Serv, FI-00079 Helsinki, Finland
[7] Univ Appl Sci, Helsinki Metropolia, Bldg Serv, FI-00079 Helsinki, Finland
[8] Univ Turku, Dept Geog & Geol, FI-20014 Turku, Finland
关键词
remote sensing; forest inventory; GIS; forest management planning; laser scanning; terrestrial laser scanning; timber quality; forest technology; NEAREST-NEIGHBOR IMPUTATION; FOREST INVENTORY; TREE ATTRIBUTES; LIDAR; PREDICTION; COMBINATION; VARIABLES; HEIGHT; LEVEL;
D O I
10.3390/f5081879
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
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.
引用
收藏
页码:1879 / 1895
页数:17
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