Journal of Remote Sensing (Jan 2022)

Estimation of Larch Growth at the Stem, Crown, and Branch Levels Using Ground-Based LiDAR Point Cloud

  • Shuangna Jin,
  • Wuming Zhang,
  • Jie Shao,
  • Peng Wan,
  • Shun Cheng,
  • Shangshu Cai,
  • Guangjian Yan,
  • Aiguang Li

DOI
https://doi.org/10.34133/2022/9836979
Journal volume & issue
Vol. 2022

Abstract

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Tree growth is an important indicator of forest health and can reflect changes in forest structure. Traditional tree growth estimates use easy-to-measure parameters, including tree height, diameter at breast height, and crown diameter, obtained via forest in situ measurements, which are labor intensive and time consuming. Some new technologies measure the diameter of trees at different positions to monitor the growth trend of trees, but it is difficult to take into account the growth changes at different tree levels. The combination of terrestrial laser scanning and quantitative structure modeling can accurately estimate tree structural parameters nondestructively and has the potential to estimate tree growth from different tree levels. In this context, this paper estimates tree growth from stem-, crown-, and branch-level attributes observed by terrestrial laser scanning. Specifically, tree height, diameter at breast height, stem volume, crown diameter, crown volume, and first-order branch volume were used to estimate the growth of 55-year-old larch trees in Saihanba of China, at the stem, crown, and branch levels. The experimental results showed that tree growth is mainly reflected in the growth of the crown, i.e., the growth of branches. Compared to one-dimensional parameter growth (tree height, diameter at breast height, or crown diameter), three-dimensional parameter growth (crown, stem, and first-order branch volumes) was more obvious, in which the absolute growth of the first-order branch volume is close to the stem volume. Thus, it is necessary to estimate tree growth at different levels for accurate forest inventory.