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Design and Implementation of System for Estimating Diameter at Breast Height and Tree Height using LiDAR point cloud data

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(2), pp.99-110
  • DOI : 10.9708/jksci.2023.28.02.099
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 26, 2023
  • Accepted : February 15, 2023
  • Published : February 28, 2023

Jong-Su Yim ORD ID 1 Dong-Hyeon Kim 2 Chi-Ung Ko 1 Dong-Geun Kim ORD ID 2 Hyung-Ju Cho 2

1국립산림과학원
2경북대학교

Accredited

ABSTRACT

In this paper, we propose a system termed ForestLi that can accurately estimate the diameter at breast height (DBH) and tree height using LiDAR point cloud data. The ForestLi system processes LiDAR point cloud data through the following steps: downsampling, outlier removal, ground segmentation, ground height normalization, stem extraction, individual tree segmentation, and DBH and tree height measurement. A commercial system, such as LiDAR360, for processing LiDAR point cloud data requires the user to directly correct errors in lower vegetation and individual tree segmentation. In contrast, the ForestLi system can automatically remove LiDAR point cloud data that correspond to lower vegetation in order to improve the accuracy of estimating DBH and tree height. This enables the ForestLi system to reduce the total processing time as well as enhance the accuracy of accuracy of measuring DBH and tree height compared to the LiDAR360 system. We performed an empirical study to confirm that the ForestLi system outperforms the LiDAR360 system in terms of the total processing time and accuracy of measuring DBH and tree height.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.