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, 21:295 | Cite as

Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR

  • Nicholas C. CoopsEmail author
  • Thomas Hilker
  • Michael A. Wulder
  • Benoît St-Onge
  • Glenn Newnham
  • Anders Siggins
  • J. A. (Tony) Trofymow
Original Paper

Abstract

Variations in vertical and horizontal forest structure are often difficult to quantify as field-based methods are labour intensive and passive optical remote sensing techniques are limited in their capacity to distinguish structural changes occurring below the top of the canopy. In this study the capacity of small footprint (0.19 cm), discrete return, densely spaced (0.7 hits/m−2), multiple return, Light Detection and Ranging (LiDAR) technology, to measure foliage height and to estimate several stand and canopy structure attributes is investigated. The study focused on six Douglas-fir [Pseudotsuga menziesii spp. menziesii (Mirb.) Franco] and western hemlock [Tsuga heterophylla (Raf.) Sarg.] stands located on the east coast of Vancouver Island, British Columbia, Canada, with each stand representing a different structural stage of stand development for forests within this biogeoclimatic zone. Tree height, crown dimensions, cover, and vertical foliage distributions were measured in 20 m × 20 m plots and correlated to the LiDAR data. Foliage profiles were then fitted, using the Weibull probability density function, to the field measured crown dimensions, vertical foliage density distributions and the LiDAR data at each plot. A modified canopy volume approach, based on methods developed for full waveform LiDAR observations, was developed and used to examine the vertical and horizontal variation in stand structure. Results indicate that measured stand attributes such as mean stand height, and basal area were significantly correlated with LiDAR estimates (r 2 = 0.85, P < 0.001, SE = 1.8 m and r 2 = 0.65, P < 0.05, SE = 14.8 m2 ha−1, respectively). Significant relationships were also found between the LiDAR data and the field estimated vertical foliage profiles indicating that models of vertical foliage distribution may be robust and transferable between both field and LiDAR datasets. This study demonstrates that small footprint, discrete return, LiDAR observations can provide quantitative information on stand and tree height, as well as information on foliage profiles, which can be successfully modelled, providing detailed descriptions of canopy structure.

Keywords

Airborne LiDAR Canopy structure Vertical foliage profiles Weibull Canopy volume profiles Remote sensing 

Notes

Acknowledgments

We thank David Seeman, Bob Ferris (Canadian Forest Service) and Rachelle Lalonde (UBC) for field assistance. Prof. Andy Black and staff allowed access to the FLUXNET—Canada site. We thank forest companies Timberwest and Weyerhaeuser for providing access to their forest inventories of the area and access to their private lands. We acknowledge staff from the CSIRO Canopy LiDAR project, in particular Dr. Jenny Lovell, for assistance with the development of the in-house software used for the analysis of the LiDAR data. The LiDAR data was acquired by Benoît St-Onge as part of an ongoing collaborative project with funds provided by NSERC and BIOCAP. Components of this research were also funded by a NSERC Discovery grant to Coops and DAAD post-graduate scholarship to Hilker. Preparation of the combined forest inventory and disturbance coverages was done partially through Action Plan 2000 and FLUXNET—CCAF funding to T. Trofymow. Finally, we are grateful to the two anonymous reviewers who provided editorial suggestions.

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Nicholas C. Coops
    • 1
    Email author
  • Thomas Hilker
    • 1
  • Michael A. Wulder
    • 2
  • Benoît St-Onge
    • 3
  • Glenn Newnham
    • 4
  • Anders Siggins
    • 4
  • J. A. (Tony) Trofymow
    • 2
  1. 1.Department of Forest Resource ManagementUniversity of British ColumbiaVancouverCanada
  2. 2.Canadian Forest Service (Pacific Forestry Centre)Natural Resources CanadaVictoriaCanada
  3. 3.Department of GeographyUniversité of Québec in MontréalMontréalCanada
  4. 4.CSIRO Forestry and Forest ProductsClayton SouthAustralia

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