rLiDAR (version 0.1)

rMetrics: Individual tree LiDAR metrics

Description

This funtion computes LiDAR-based statistic metrics for individual trees detected from the 3D LiDAR point cloud.

Usage

rMetrics(xyziId)

Arguments

xyziId

A 5-column matrix with the x, y, z coordinates, intensity and the tree id classification for the LiDAR point cloud.

Value

Returns A matrix of the LiDAR-based metrics for the individual tree detected.

Details

# List of the individual tree LiDAR metrics:

# Total number of returns (TotalReturns); # UTM Easting coordinate of the tree top (Etop); # UTM Northing coordinate of the tree top (Ntop); # Minimum UTM Easting coordinate (Emin); # Minimum UTM Northing coordinate (Nmin); # Maximum UTM Easting coordinate (Emax); # Maxmium UTM Northing coordinate (Nmax); # Tree crown width 01 (Ewidth); # Tree crown width 02 (Nwidth); # Maximum Height (hmax); # Mean height (hmean); # Standard deviation of height (hsd); # Coefficient of variation of height (hcv); # Mode of height (hmod); # 5th percentile of height (h5); # 10th percentile of height (h10); # 20th percentile of height (h20); # 25th percentile of height (h25); # 30th percentile of height (h30); # 40th percentile of height (h40); # 50th percentile of height (h50); # 60th percentile of height (h60); # 70th percentile of height (h70); # 75th percentile of height (h75); # 80th percentile of height (h80); # 90th percentile of height (h90); # 95th percentile of height (h95); # 99th percentile of height (h99); # Maximum intensity (imax); # Mean intensity (imean); # Standard deviation of intensity (isd); # Coefficient of variation of intensity (icv); # Mode of intensity (imod); # 5th percentile of intensity (i5); # 10th percentile of intensity (i10); # 20th percentile of intensity (i20); # 25th percentile of intensity (i25); # 30th percentile of intensity (i30); # 40th percentile of intensity (i40); # 50th percentile of intensity (i50); # 60th percentile of intensity (i60); # 70th percentile of intensity (i70); # 75th percentile of intensity (i75); # 80th percentile of intensity (i80); # 90th percentile of intensity (i90); # 95th percentile of intensity (i95); # 99th percentile of intensity (i99).

Examples

# NOT RUN {
#=======================================================================#
# Individual tree detection using K-means cluster
#=======================================================================#
# Importing LAS file:
LASfile <- system.file("extdata", "LASexample1.las", package="rLiDAR")

# Reading LAS file
LAS<-readLAS(LASfile,short=TRUE)

# Setting the xyz coordinates and subsetting the data
xyzi<-subset(LAS[,1:4],LAS[,3] >= 1.37)

# Finding clusters (trees)
clLAS<-kmeans(xyzi[,1:2], 32)

# Set the tree id vector
Id<-as.factor(clLAS$cluster)

# Combining xyzi and tree id
xyziId<-cbind(xyzi,Id)

#=======================================================================#
#  Computing individual tree LiDAR metrics
#=======================================================================#

TreesMetrics<-rMetrics(xyziId)
head(TreesMetrics)
# }