tree_summary: Tree point cloud summary function

In RCBlackburn/lidRmts: Area based lidar attributes

Tree point cloud summary function

Description

This function provides individual tree-based variables including number of trees (ntrees), height of trees (ht), number of points per tree (npts), and crown area (ca). These variables are summarized for the entire point cloud including the mean, median, variance, standard deviation, coefficient of variation, IQR, skewness, and kurtosis

Usage

tree_summary(las)

Arguments

las	las object with tree ID column

Examples

LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile)
las <- filter_poi(las, Classification != LASNOISE)
las <- normalize_height(las, knnidw(k = 8, p = 2))
las <- filter_poi(las, Z < 50 & Z >= 1.37 )
las <- decimate_points(las, random_per_voxel(res = 1, n = 8))
las_tree <- segment_trees(las, li2012())
tree_metrics <- tree_summary(las_tree)
print(tree_metrics)

RCBlackburn/lidRmts documentation built on Aug. 2, 2024, 11:21 a.m.