Estimation of diameter and height tree-wise for normalized point clouds with assigned stem points.
tlsInventory(
las,
dh = 1.3,
dw = 0.5,
hp = 1,
d_method = shapeFit(shape = "circle", algorithm = "ransac", n = 15, n_best = 20)
)
LAS
object.
numeric
- height layer (above ground) to estimate stem diameters, in point cloud units.
numeric
- height layer width, in point cloud units.
numeric
- height percentile to extract per tree (0-1). Use 1 for top height, i.e. the highest point.
parameterized shapeFit
function, i.e. method to use for diameter estimation.
# NOT RUN {
file = system.file("extdata", "pine_plot.laz", package="TreeLS")
tls = readTLS(file) %>%
tlsNormalize %>%
tlsSample
map = treeMap(tls, map.hough())
tls = treePoints(tls, map, trp.crop(circle=FALSE))
tls = stemPoints(tls, stm.hough())
dmt = shapeFit(shape = 'circle', algorithm='ransac', n=20)
inv = tlsInventory(tls, d_method = dmt)
tlsPlot(tls, inv)
# }
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