Detailed Stem Measurements of Standing Trees from Ground-Based Scanning Lidar

By J. Henning, P. Radtke. Forestry sciences, 2006

249 citations recorded by the source corpus.

A commercially available pan-and-tilt mount laser scanner was used to acquire data for subsequent three-dimensional modeling and measurement of standing forest trees. Methods were developed for identifying trees in range images and co-registering range images acquired from different vantage points. Upper-stem diameters and branch heights derived from the range images were compared to measurements made after the felling of a small number of loblolly pine (Pinus taeda L.) trees. Tree identification assumed bole cross-sections were circular, estimating their geometric centers at successive heights up the stem. Tree center estimates at multiple heights were then used to co-register images made from different vantage points. Co-registration (x, y) errors did not exceed 2.1 cm in any of the 18 pairwise registrations carried out. Results showed excellent agreement (average error < 1 cm) between the lidar-derived diameter estimates and caliper measurements for bole sections below the base of live crown. Less accurate estimates (<2 cm) were obtained for stem heights up to 13 m. Results indicated the potential for accurate assessment of branch or whorl heights using ground-based scanning lidar, with the greatest accuracy likely to be realized for branches near the base of the live crown and below it.

Subfields: Environmental Engineering, Mechanical Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/c1953f6dc16a89249c24c1fb0dcd4c2d657e8a2f

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Citations in the corpus

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors (2009, methodology): “to investigate forest health [27,28], forest stand structure and biophysical parameters [29-33].”
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (2013, methodology): “In forest research, TLS has been used for the detailed modeling of individual trees and canopies [7,8,11,13,14].”
International benchmarking of terrestrial laser scanning approaches for forest inventories (2018, background): “The past two decades have witnessed steady progress in these types of studies (Henning and Radtke, 2006; Hosoi and Omasa, 2006; Lefsky and McHale, 2008; Maas et al., 2008; Strahler et al., 2008; Côté et al., 2009; Jupp et al., 2009; Tansey et al., 2009).”
3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates (2015, background): “Hopkinson et al. (2004) underestimated the heights f mature, plantation-grown red pine and sugar maple in a mixed eciduous forest by roughly 7% which was due to occlusion of the op of trees. Likewise, Maas et al. (2008) underestimated the heights f mature mixed and coniferous forest plots dominated ”
Deriving Merchantable Volume in Poplar through a Localized Tapering Function from Non-Destructive Terrestrial Laser Scanning (2016, methodology): “This necessitates the use of reference points as a means for correctly matching coordinate positions [22].”
Volume estimates of trees with complex architecture from terrestrial laser scanning (2008, background): “Henning and Radke [8] also focused on main stems, although their goal was to accurately measure upper stem diameters that are also difficult to evaluate without labor-intensive or destructive methods.”
Capturing tree crown formation through implicit surface reconstruction using airborne lidar data (2009, background): “…of tree parameters (Chasmer et al., 2006), inability to distinguish between laser returns from foliage and stems (Clawges et al., 2007), andmisalignment of points captured by different vantage points (Henning & Radtke, 2006) continue to challenge verification methods that employ ground lidar.”
Estimation of stem attributes using a combination of terrestrial and airborne laser scanning (2012, methodology): “…(Bienert et al. 2007; Király and Brolly 2007; Maas et al. 2008), skeletonization (Gorte and Pfeifer 2004), or the Hough transform (Aschoff et al. 2004), and then fit circles along the tree stems using least squares regression (Henning and Radtke 2006; Watt and Donoghue 2005; Pfeifer et al. 2004).”
Automatic forest inventory parameter determination from terrestrial laser scanner data (2008, methodology): “The circle fitting procedure, which is similar to the one described by Henning and Radtke (2006), is applied recursively.”
Quantifying branch architecture of tropical trees using terrestrial LiDAR and 3D modelling (2018, background): “2006) and generate a limited number of attributes that can be readily obtained with nondestructive methods (Henning and Radtke 2006.”