Abstract

The value of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), which is the predominant commercial species in the Pacific Northwest, depends on tree verticality; trees with the same dimensions can differ substantially in value due to lean. The objective of this study was to assess the impact of tree leaning on estimation of stem dimensions using high-density terrestrial mobile lidar point clouds. We estimated lean with two metrics: the horizontal distance between stem centers at 1.3 m and 18 m, and the mean of seven successive lean angles along the tree bole (at 1, 3, 5, 7, 10, 12, and 15 m). For modeling, we used four existing taper equations and three existing volume equations. For trees leaning >2°, we enhanced the existing volume models by including lean as a predictor. Because lean estimates depend on the distribution and number of points describing the stem, we found that including the distance from scanner to tree improved the computed volume. When diameter at breast height was replaced with diameter at heights between 7 and 10 m, the volume models for leaning trees improved significantly, whereas the vertical trees had favorable results with heights between 5 and 15 m. Our study suggests that lean magnitude improves the estimation of stem volume when lean is >2°.

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