Detection of individual trees and estimation of tree height using LiDAR data

Doo Ahn Kwak, Woo-Kyun Lee, Jun Hak Lee, Greg S. Biging, Peng Gong

Research output: Contribution to journalArticle

143 Citations (Scopus)


For estimation of tree parameters at the single-tree level using light detection and ranging (LiDAR), detection and delineation of individual trees is an important starting point. This paper presents an approach for delineating individual trees and estimating tree heights using LiDAR in coniferous (Pinus koraiensis, Larix leptolepis) and deciduous (Quercus spp.) forests in South Korea. To detect tree tops, the extended maxima transformation of morphological image-analysis methods was applied to the digital canopy model (DCM). In order to monitor spurious local maxima in the DCM, which cause false tree tops, different h values in the extended maxima transformation were explored. For delineation of individual trees, watershed segmentation was applied to the distance-transformed image from the detected tree tops. The tree heights were extracted using the maximum value within the segmented crown boundary. Thereafter, individual tree data estimated by LiDAR were compared to the field measurement data under five categories (correct delineation, satisfied delineation, merged tree, split tree, and not found). In our study, P. koraiensis, L. leptolepis, and Quercus spp. had the best detection accuracies of 68.1% at h = 0.18, 86.7% at h = 0.12, and 67.4% at h = 0.02, respectively. The coefficients of determination for tree height estimation were 0.77, 0.80, and 0.74 for P. koraiensis, L. leptolepis, and Quercus spp., respectively.

Original languageEnglish
Pages (from-to)425-434
Number of pages10
JournalJournal of Forest Research
Issue number6
Publication statusPublished - 2007 Dec 1


  • Individual trees
  • LiDAR
  • Morphological image analysis
  • Tree height
  • Tree top

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)

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