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Modeling Crown Structure from LiDAR Data with Statistical Distributions

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The objective of this study was to evaluate the ability of three statistical distributions to characterize the vertical distribution of foliage mass in canopies of even-aged loblolly pine stands, based on airborne-scanning light detection and ranging (LiDAR) data. The functions were the Weibull and SB distributions and a mixture of the lognormal and Weibull distributions. Results indicated that the mixture distribution fit the LiDAR data better than the Weibull and SB distributions, according to three goodness-of-fit statistics. By switching from the lognormal for data near the tree top to the Weibull for data near the base of the crown, the mixture distribution seemed to better resemble the shape of the distribution of LiDAR returns than the Weibull alone. The mixture distribution was particularly effective for plots in which distributions of the returns were too peaked for either the Weibull or SB.

Keywords: SB; Weibull; canopy; foliage distribution; loblolly pine; lognormal; mixture

Document Type: Research Article

Publication date: 2011-10-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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