Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds

Hamid Hamraz, Marco A. Contreras, Jun Zhang

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each layer using a digital surface model based tree segmentation method. The novelty of the approach is the stratification procedure that separates the point cloud to an overstory and multiple understory tree canopy layers by analyzing vertical distributions of LiDAR points within overlapping locales. The procedure does not make a priori assumptions about the shape and size of the tree crowns and can, independent of the tree segmentation method, be utilized to vertically stratify tree crowns of forest canopies. We applied the proposed approach to the University of Kentucky Robinson Forest – a natural deciduous forest with complex and highly variable terrain and vegetation structure. The segmentation results showed that using the stratification procedure strongly improved detecting understory trees (from 46% to 68%) at the cost of introducing a fair number of over-segmented understory trees (increased from 1% to 16%), while barely affecting the overall segmentation quality of overstory trees. Results of vertical stratification of the canopy showed that the point density of understory canopy layers were suboptimal for performing a reasonable tree segmentation, suggesting that acquiring denser LiDAR point clouds would allow more improvements in segmenting understory trees. As shown by inspecting correlations of the results with forest structure, the segmentation approach is applicable to a variety of forest types.

Original languageEnglish
Pages (from-to)385-392
Number of pages8
JournalISPRS Journal of Photogrammetry and Remote Sensing
StatePublished - Aug 2017

Bibliographical note

Publisher Copyright:
© 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)


  • Canopy layering
  • Discrete return LiDAR
  • Individual tree segmentation
  • Multi-story stand
  • Remote sensing

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences


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