The Influence of Cross-Section Thickness on Diameter at Breast Height Estimation from Point Cloud

Circle-fitting methods are commonly used to estimate diameter at breast height (DBH) of trees from horizontal cross-section of point clouds. In this paper, we addressed the problem of cross-section thickness optimization regarding DBH estimation bias and accuracy. DBH of 121 European beeches (Fagus sylvatica L.) and 43 Sessile oaks (Quercus petraea (Matt.) Liebl.) was estimated from cross-sections with thicknesses ranging from 1 to 100 cm. The impact of cross-section thickness on the bias, standard error, and accuracy of DBH estimation was statistically significant. However, the biases, standard errors, and accuracies of DBH estimation were not significantly different among 1–10-cm cross-sections, except for oak DBH estimation accuracy from an 8-cm cross-section. DBH estimations from 10–100-cm cross-sections were considerably different. These results provide insight to the influence of cross-section thickness on DBH estimation by circle-fitting methods, which is beneficial for point cloud data acquisition planning and processing. The optimal setting of cross-section thickness facilitates point cloud processing and DBH estimation by circle-fitting algorithms.

[1]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[2]  Thomas Udelhoven,et al.  The influence of scan mode and circle fitting on tree stem detection, stem diameter and volume extraction from terrestrial laser scans , 2013 .

[3]  M. Koren,et al.  Use of terrestrial laser scanning to evaluate the spatial distribution of soil disturbance by skidding operations , 2014 .

[4]  Sorin C. Popescu,et al.  Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter , 2015, Remote. Sens..

[5]  Juha Hyyppä,et al.  The effect of TLS point cloud sampling on tree detection and diameter measurement accuracy , 2016 .

[6]  Ahmad Kamal Aijazi,et al.  Automatic Detection and Parameter Estimation of Trees for Forest Inventory Applications Using 3D Terrestrial LiDAR , 2017, Remote. Sens..

[7]  Martin Mokros,et al.  Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[8]  Julia Armesto,et al.  Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning , 2018, Int. J. Appl. Earth Obs. Geoinformation.

[9]  K. Rajan,et al.  Automatic Tree Identification and Diameter Estimation Using Single Scan Terrestrial Laser Scanner Data in Central Indian Forests , 2018, Journal of the Indian Society of Remote Sensing.

[10]  Xin Tian,et al.  Evaluating Different Methods for Estimating Diameter at Breast Height from Terrestrial Laser Scanning , 2018, Remote. Sens..

[11]  Jinliang Wang,et al.  Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level , 2018, Forests.

[12]  Francesca Giannetti,et al.  Comparing Three Different Ground Based Laser Scanning Methods for Tree Stem Detection , 2018, Remote. Sens..

[13]  M. Vastaranta,et al.  Assessing branching structure for biomass and wood quality estimation using terrestrial laser scanning point clouds , 2018, Canadian Journal of Remote Sensing.

[14]  Annika Kangas,et al.  Measuring stem diameters with TLS in boreal forests by complementary fitting procedure , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[15]  Christoph Gollob,et al.  Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots , 2019, Remote. Sens..

[16]  N. Puletti,et al.  Evaluating the Eccentricities of Poplar Stem Profiles with Terrestrial Laser Scanning , 2019, Forests.

[17]  Juha Hyyppä,et al.  In situ biomass estimation at tree and plot levels: What did data record and what did algorithms derive from terrestrial and aerial point clouds in boreal forest , 2019, Remote Sensing of Environment.

[18]  Li Li,et al.  Analysis of Parameters for the Accurate and Fast Estimation of Tree Diameter at Breast Height Based on Simulated Point Cloud , 2019, Remote. Sens..

[19]  Christian Ginzler,et al.  A Single-Tree Processing Framework Using Terrestrial Laser Scanning Data for Detecting Forest Regeneration , 2018, Remote. Sens..

[20]  Juha Hyyppä,et al.  Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests , 2019, Remote. Sens..

[21]  Juha Hyyppä,et al.  Examining Changes in Stem Taper and Volume Growth with Two-Date 3D Point Clouds , 2019, Forests.