LiDARForestStand: 3D stand visualization of LiDAR-derived individual trees

In rLiDAR: LiDAR Data Processing and Visualization

Description

Draws a 3D scatterplot for individual trees detected from Lidar data.

Usage

LiDARForestStand(crownshape = c("cone", "ellipsoid", "halfellipsoid",
                "paraboloid", "cylinder"), CL = 4, CW = 8, HCB = 10, 
                  X = 0, Y = 0, dbh = 0.3, crowncolor = "forestgreen", 
                 stemcolor = "chocolate4", resolution="high", mesh=TRUE)

Arguments

crownshape	shape of individual tree crown: "cone", "ellipsoid","halfellipsoid", "paraboloid" or "cylinder". Default is "halfellipsoid".
CL	crown length.
CW	crown diameter.
HCB	height at canopy base.
X	x-coordinate.
Y	y-coordinate.
dbh	diameter at breast height (1.73 m).
crowncolor	crown color.
stemcolor	stem color.
resolution	crown resolution: "low", "medium" and "high".
mesh	Logical, if TRUE (default) returns a tree crown mesh model, and if FALSE returns a tree crown line mode.

Value

Returns a 3-D scatterplot of the individual trees as identified automatically from the LiDAR.

Author(s)

Carlos Alberto Silva and Remko Duursma. Uses code by Remko Duursma (Maeswrap package,see "Plotstand").

References

https://maespa.github.io/

Examples

#=======================================================================#
# EXAMPLE 01: Plotting single trees
#=======================================================================#

# cone crown shape
library(rgl)
open3d() 
LiDARForestStand(crownshape = "cone", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=TRUE) 
                       
# ellipsoid crown shape 
open3d()
LiDARForestStand(crownshape = "ellipsoid", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=TRUE) 
                       
# halfellipsoid crown shape 
open3d()
LiDARForestStand(crownshape = "halfellipsoid", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=TRUE) 
                       
# paraboloid crown shape 
open3d()
LiDARForestStand(crownshape = "paraboloid", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=TRUE)

# cylinder crown shape 
open3d()
LiDARForestStand(crownshape = "cylinder", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=TRUE)
                       
# Set the shape=FALSE 
open3d()
LiDARForestStand(crownshape = "paraboloid", CL = 10, CW =7, 
           HCB = 5, X =0, Y = 0, dbh = 0.4, crowncolor = "forestgreen", 
           stemcolor = "chocolate4", resolution="high", mesh=FALSE)

#=======================================================================#
#EXAMPLE 02: Plotting a forest plantation stand in virtual 3-D space
#=======================================================================#

# Set the dimensions of the displayed forest stand
xlength<-30 # x length
ylength<-20 # y length

# Set the space between trees
sx<-3 # x space length
sy<-2 # y space length

# Tree location grid
XYgrid <- expand.grid(x = seq(1,xlength,sx), y = seq(1,ylength,sy))

# Get the number of trees
Ntrees<-nrow(XYgrid)

# Plot a virtual Eucalyptus forest plantation stand using the halfellipsoid tree crown shape

# Set stand trees parameters
meanHCB<-5  # mean of the height at canopy base
sdHCB<-0.1  # standard deviation of the height at canopy base
HCB<-rnorm(Ntrees, mean=meanHCB, sd=sdHCB) # height at canopy base
CL<-HCB     # tree crown height
CW<-HCB*0.6 # tree crown diameter

open3d()    # open a rgl window

# Plotting the stand
for( i in 1:Ntrees){
 LiDARForestStand(crownshape = "halfellipsoid", CL = CL[i], CW = CW[i], 
             HCB = HCB[i], X = XYgrid[i,1], Y = XYgrid[i,2], dbh = 0.4, 
             crowncolor = "forestgreen", stemcolor = "chocolate4", 
             resolution="high", mesh=TRUE) 
}
                           
# Add other plot parameters
axes3d(c("x-", "x-", "y-", "z"), col="gray")       # axes
title3d(xlab = "X Coord", ylab = " Y Coord", zlab = "Height", col="red") # title
planes3d(0, 0, -1, 0.001, col="gray", alpha=0.7)   # set a terrain plane


# Plotting a virtual single-species forest plantation stand using "cone" tree crown shape

# Set parameters f trees growing within the virtual stand
meanHCB<-3  # mean of the height at canopy base
sdHCB<-0.1  # standard deviation of the height at canopy base
HCB<-rnorm(Ntrees, mean=meanHCB, sd=sdHCB) # height at canopy base
CL<-HCB*2.0 # tree crown height
CW<-HCB*1.3 # tree crown diameter

open3d() # open a rgl window
# Plot stand
for( i in 1:Ntrees){
 LiDARForestStand(crownshape = "cone", CL = CL[i], CW = CW[i], 
             HCB = HCB[i], X = XYgrid[i,1], Y = XYgrid[i,2], dbh = 0.4, 
             crowncolor = "forestgreen", stemcolor = "chocolate4", 
             resolution="high", mesh=TRUE) 
}
                           
# Add other plot parameters
axes3d(c("x-", "x-", "y-", "z"), col="gray")       # axes
title3d(xlab = "X Coord", ylab = " Y Coord", zlab = "Height", col="red") # title
planes3d(0, 0, -1, 0.001, col="gray", alpha=0.7)   # set a terrain plane

#=======================================================================#
# EXAMPLE 03: Plotting a virtual mixed forest stand
#=======================================================================#

# 01. Plot different trees species in the stand with different crown shapes 

# Set the number of trees
Ntrees<-80 

# Set the trees locations
xcoord<-sample(1:100, Ntrees)  # x coord
ycoord<-sample(1:100, Ntrees)  # y coord

# Set a location grid of trees 
XYgrid<-cbind(xcoord,ycoord)

# Plot the location of the trees
plot(XYgrid, main="Tree location")

meanHCB<-7 # mean of the height at canopy base
sdHCB<-3   # standard deviation of height at canopy base
HCB<-rnorm(Ntrees, mean=meanHCB, sd=sdHCB) # height at canopy base
crownshape<-sample(c("cone", "ellipsoid","halfellipsoid", 
                  "paraboloid"), Ntrees, replace=TRUE) # tree crown shape 
CL<-HCB*1.3 # tree crown height
CW<-HCB     # tree crown diameter

open3d() # open a rgl window
# Plot stand

for( i in 1:Ntrees){
 LiDARForestStand(crownshape = crownshape[i], CL = CL[i], CW = CW[i], 
             HCB = HCB[i], X = as.numeric(XYgrid[i,1]), Y = as.numeric(XYgrid[i,2]), 
             dbh = 0.4, crowncolor = "forestgreen", stemcolor = "chocolate4", 
             resolution="high", mesh=TRUE)
}
                         
# Add other plot parameters
axes3d(c("x-", "x-", "y-", "z"), col="gray")       # axes
title3d(xlab = "X Coord", ylab = " Y Coord", zlab = "Height", col="red") # title
planes3d(0, 0, -1, 0.001, col="gray", alpha=0.7)   # set a terrain plane


# 02. Plot different tree height in the stand using different crown colors

# Set the number of trees
Ntrees<-80 

# Set the tree locations
xcoord<-sample(1:100, Ntrees) # x coord
ycoord<-sample(1:100, Ntrees) # y coord

# Set a location grid of trees 
XYgrid<-cbind(xcoord,ycoord)

# plot the location of the trees
plot(XYgrid, main="Tree location")

meanHCB<-7 # mean of the height at canopy base
sdHCB<-3   # standard deviation of the height at canopy base
HCB<-rnorm(Ntrees, mean=meanHCB, sd=sdHCB) # height at canopy base
crownshape<-sample(c("cone", "ellipsoid","halfellipsoid", "paraboloid"), 
                  Ntrees, replace=TRUE) # tree crown shape 
CL<-HCB*1.3 # tree crown height
CW<-HCB     # tree crown diameter

# Plot tree height based on the HCB quantiles
HCBq<-quantile(HCB) # HCB quantiles
crowncolor<-NA*(1:Ntrees) # set an empty crowncolor vector

# classify trees by HCB quantile
for (i in 1:Ntrees){
 if (HCB[i] <= HCBq[2]) {crowncolor[i]<-"red"}                        # group 1
 if (HCB[i] > HCBq[2] & HCB[i] <= HCBq[3] ) {crowncolor[i]<-"blue"}   # group 2
 if (HCB[i] > HCBq[3] & HCB[i] <= HCBq[4] ) {crowncolor[i]<-"yellow"} # group 3
 if (HCB[i] >= HCBq[4]) {crowncolor[i]<-"dark green"}                 # group 4
}
   
open3d() # open a rgl window

# Plot stand
for(i in 1:Ntrees){  
 LiDARForestStand(crownshape = crownshape[i], CL = CL[i], CW = CW[i], 
   HCB = HCB[i], X = as.numeric(XYgrid[i,1]), Y = as.numeric(XYgrid[i,2]), 
   dbh = 0.4, crowncolor = crowncolor[i],stemcolor = "chocolate4", 
   resolution="high", mesh=TRUE) 
}
   
# Add other plot parameters
axes3d(c("x-", "x-", "y-", "z"), col="gray")       # axes
title3d(xlab = "X Coord", ylab = " Y Coord", zlab = "Height", col="red") # title
planes3d(0, 0, -1, 0.001, col="gray", alpha=0.7)   # set a terrain plane

rLiDAR documentation built on Oct. 5, 2021, 9:07 a.m.