std_tree_metrics: Computation of tree metrics

In lidaRtRee: Forest Analysis with Airborne Laser Scanning (LiDAR) Data

Computation of tree metrics

Description

This function computes summary statistics from a data.frame containing tree-level information as returned by tree_extraction.

Usage

std_tree_metrics(x, area_ha = NA)

Arguments

x	data.frame containing the following columns for each line (segmented tree): h (height), s (crown surface), v (crown volume), typically returned by tree_extraction. sp (crown surface inside region of interest) and vp (crown volume in region of interest) are not used in this function.
area_ha	numeric. area of region of interest in ha

Value

a data.frame with one line containing the following tree metrics:

1. Tree_meanH: mean height of detected tree apices (m)

2. Tree_sdH: standard deviation of heights of detected tree apices (m)

3. Tree_giniH: Gini index of heights of detected tree apices

4. Tree_density: density of detected tree apices (/ha)

5. TreeInf10_density: density of detected trees apices with h<=10 (/ha)

6. TreeSup10_density: density of detected trees apices with h>10 (/ha)

7. TreeSup20_density: density of detected trees apices with h>20 (/ha)

8. TreeSup30_density: density of detected trees apices with h>30 (/ha)

9. Tree_meanCrownSurface: mean crown surface of detected trees

10. Tree_meanCrownVolume: mean volume of detected trees

11. TreeCanopy_meanH: mean height of union of crowns of detected trees

See Also

tree_extraction, clouds_tree_metrics, raster_metrics

Examples

# sample 50 height values
h <- runif(50, 5, 40)
# simulate tree data.frame
trees <- data.frame(h = h, s = h, sp = h * 0.95, v = h * h * 0.6, vp = h * h * 0.55)
std_tree_metrics(trees, area_ha = 0.1)

lidaRtRee documentation built on April 3, 2025, 10:29 p.m.