Modeling Crown Structure from LiDAR Data with Statistical Distributions
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.