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Research | Open Access

Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system

Yuyang Xie1,Jie Zhang1,Xiangwu Chen2Shuxin Pang3Hui Zeng1Zehao Shen2 ( )
School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China
MOE Laboratory for Earth Surface Processes, Institute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China

Yuyang Xie and Jie Zhang contributed equally to this work.

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Abstract

Background

The LiBackpack is a recently developed backpack light detection and ranging (LiDAR) system that combines the flexibility of human walking with the nearby measurement in all directions to provide a novel and efficient approach to LiDAR remote sensing, especially useful for forest structure inventory. However, the measurement accuracy and error sources have not been systematically explored for this system.

Method

In this study, we used the LiBackpack D-50 system to measure the diameter at breast height (DBH) for a Pinus sylvestris tree population in the Saihanba National Forest Park of China, and estimated the accuracy of LiBackpack measurements of DBH based on comparisons with manually measured DBH values in the field. We determined the optimal vertical slice thickness of the point cloud sample for achieving the most stable and accurate LiBackpack measurements of DBH for this tree species, and explored the effects of different factors on the measurement error.

Result

1) A vertical thickness of 30 cm for the point cloud sample slice provided the highest fitting accuracy (adjusted R2 = 0.89, Root Mean Squared Error (RMSE) = 20.85 mm); 2) the point cloud density had a significant negative, logarithmic relationship with measurement error of DBH and it explained 35.1% of the measurement error; 3) the LiBackpack measurements of DBH were generally smaller than the manually measured values, and the corresponding measurement errors increased for larger trees; and 4) by considering the effect of the point cloud density correction, a transitional model can be fitted to approximate field measured DBH using LiBackpack- scanned value with satisfactory accuracy (adjusted R2 = 0.920; RMSE = 14.77 mm), and decrease the predicting error by 29.2%. Our study confirmed the reliability of the novel LiBackpack system in accurate forestry inventory, set up a useful transitional model between scanning data and the traditional manual-measured data specifically for P. sylvestris, and implied the applicable substitution of this new approach for more species, with necessary parameter calibration.

References

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Forest Ecosystems
Article number: 33

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Cite this article:
Xie Y, Zhang J, Chen X, et al. Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system. Forest Ecosystems, 2020, 7(3): 33. https://doi.org/10.1186/s40663-020-00237-0

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Received: 13 December 2019
Accepted: 02 April 2020
Published: 09 May 2020
© The Author(s) 2020.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.