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Predicting dynamic modulus of elasticity of Norway spruce structural timber by forest inventory,airborne laser scanning and harvester-derived data
Authors:Carolin Fischer  Olav A Høibø  Geir I Vestøl  Marius Hauglin  Endre H Hansen  Terje Gobakken
Institution:1. Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences (NMBU), ?s, Norwaycarolin.fischer@nmbu.no;3. Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences (NMBU), ?s, Norway
Abstract:Norway spruce structural timber is one of the most important products of the Norwegian sawmilling industry, and a high grade-yield of structural timber is therefore important for the economic yield. Presorting of logs suited for production of structural timber might be one option to increase the grade yield. In this study, dynamic modulus of elasticity (Edyn) of structural timber was predicted based on forest inventory data at site level and single-tree data from airborne laser scanning (ALS) and harvester. The models were based on 611 boards from 4 sites in southeastern Norway. Important variables at site level were elevation, site index (SI), and mean stand age. However, when combining data from all information sources, mean stand age and site index were the only significant variables at site level. Tree height and variables describing the crown, like crown length and crown volume, were important vaiables extracted from ALS data. Stem diameter measures and tapering were important variables measured by the harvester. The combined model with variables from all three information sources reduced the variance the most, especially when using individual tree age instead of average stand age. However, combining all these data requires accurate positioning of the trees by the harvester.
Keywords:Presorting  grade yield  strength grading  timber quality  remote sensing
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