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Remote Sens. 2017, 9(7), 716; doi:10.3390/rs9070716

Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds

College of Forestry, Oregon State University, 3100 Jefferson Way, Corvallis, OR 97333, USA
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Received: 3 May 2017 / Revised: 7 July 2017 / Accepted: 9 July 2017 / Published: 12 July 2017
(This article belongs to the Section Forest Remote Sensing)
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Abstract

The estimation of tree biomass and the products that can be obtained from a tree stem have focused forest research for more than two centuries. Traditionally, measurements of the entire tree bole were expensive or inaccurate, even when sophisticated remote sensing techniques were used. We propose a fast and accurate procedure for measuring diameters along the merchantable portion of the stem at any given height. The procedure uses unreferenced photos captured with a consumer grade camera. A photogrammetric point cloud (PPC) is produced from the acquired images using structure from motion, which is a computer vision range imaging technique. A set of 18 loblolly pines (Pinus taeda Lindl.) from east Louisiana, USA, were photographed, subsequently cut, and the diameter measured every meter. The same diameters were measured on the point cloud with AutoCAD Civil3D. The ground point cloud reconstruction provided useful information for at most 13 m along the stem. The PPC measurements are biased, overestimating real diameters by 17.2 mm, but with a reduced standard deviation (8.2%). A linear equation with parameters of the error at a diameter at breast height (d1.3) and the error of photogrammetric rendering reduced the bias to 1.4 mm. The usability of the PPC measurements in taper modeling was assessed with four models: Max and Burkhart [1], Baldwin and Feduccia [2], Lenhart et al. [3], and Kozak [4]. The evaluation revealed that the data fit well with all the models (R2 ≥ 0.97), with the Kozak and the Baldwin and Feduccia performing the best. The results support the replacement of taper with PPC, as faster, and more accurate and precise product estimations are expected. View Full-Text
Keywords: structure from motion; merchantable stem; bias; accuracy; precision structure from motion; merchantable stem; bias; accuracy; precision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Fang, R.; Strimbu, B.M. Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds. Remote Sens. 2017, 9, 716.

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