lmfauto: Individual Tree Detection Algorithm

In Jean-Romain/lidRplugins: Extra functions and algorithms for lidR package

Individual Tree Detection Algorithm

Description

This function is made to be used in find_trees. It implements a fast and parameter-free algorithm for individual tree detection for broad coverage. It is based on two local maximum filters (LMF). The first pass performs a very rough estimation of the number of trees with a fixed window size. Based on this rough estimate it automatically computes a variable windows size LMF with workable parameters. This algorithm is made to process wide areas rather than small plots. See references for more details.

Usage

lmfauto(plot = FALSE, hmin = 2)

Arguments

plot	logical set it to TRUE if processing a plot instead of a large area. What changes is the estimation of the local number of trees. It should be based on the local neighborhood for the general case but this does not make sense for a plot.
hmin	numeric. Minimum height of a tree. Threshold below which a point cannot be a local maxima. Default is 2.

References

Jean-Romain Roussel, Francesco Pirotti, Luiz Carlos Estraviz Rodriguez, Jean-François Bourdon, Antoine Lebœuf, Marc-Olivier Lemonde, Alexis Achim. Development of an auto-adaptive individual tree detection algorithm for airborne LiDAR data (in prep.)

See Also

Other individual tree detection algorithms: LayerStacking(), multichm(), ptrees()

Examples

LASfile <- system.file("extdata", "MixedConifer.laz", package="lidR")
las <- readLAS(LASfile)
ttops <- find_trees(las, lmfauto())

x = plot(las)
add_treetops3d(x, ttops)

Jean-Romain/lidRplugins documentation built on Feb. 8, 2023, 5:39 a.m.