# NOT RUN {
LASfile <- system.file("extdata", "MixedConifer.laz", package="lidR")
poi = "-drop_z_below 0 -inside 481280 3812940 481330 3812990"
las <- readLAS(LASfile, filter = poi)
col <- height.colors(50)
# Basic triangulation and rasterization of first returns
chm <- grid_canopy(las, res = 0.5, dsmtin())
plot(chm, col = col)
# Khosravipour et al. pitfree algorithm
chm <- grid_canopy(las, res = 0.5, pitfree(c(0,2,5,10,15), c(0, 1.5)))
plot(chm, col = col)
# }
# NOT RUN {
# Potentially complex concave subset of point cloud
x = c(481340, 481340, 481280, 481300, 481280, 481340)
y = c(3812940, 3813000, 3813000, 3812960, 3812940, 3812940)
las2 = clip_polygon(las,x,y)
plot(las2)
# Since the TIN interpolation is done within the convex hull of the point cloud
# dummy pixels are interpolated that are strictly correct according to the interpolation method
# used, but meaningless in our CHM
chm <- grid_canopy(las2, res = 0.5, pitfree())
plot(chm, col = col)
chm = grid_canopy(las2, res = 0.5, pitfree(max_edge = c(3, 1.5)))
plot(chm, col = col)
# }
Run the code above in your browser using DataLab