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Region growing

Source: R/stages.R
region_growing.Rd

Region growing for individual tree segmentation based on Dalponte and Coomes (2016) algorithm (see reference). Note that this stage strictly performs segmentation, while the original method described in the manuscript also performs pre- and post-processing tasks. Here, these tasks are expected to be done by the user in separate functions.

Usage

region_growing(
  raster,
  seeds,
  th_tree = 2,
  th_seed = 0.45,
  th_cr = 0.55,
  max_cr = 20,
  ofile = temptif()
)

Arguments

raster

LASRalgoritm. A stage producing a raster.

seeds

LASRalgoritm. A stage producing points used as seeds.

th_tree

numeric. Threshold below which a pixel cannot be a tree. Default is 2.

th_seed

numeric. Growing threshold 1. See reference in Dalponte et al. 2016. A pixel is added to a region if its height is greater than the tree height multiplied by this value. It should be between 0 and 1. Default is 0.45.

th_cr

numeric. Growing threshold 2. See reference in Dalponte et al. 2016. A pixel is added to a region if its height is greater than the current mean height of the region multiplied by this value. It should be between 0 and 1. Default is 0.55.

max_cr

numeric. Maximum value of the crown diameter of a detected tree (in data units). Default is 20. BE CAREFUL this algorithm exists in the lidR package and this parameter is in pixels in lidR.

ofile

character. Full outputs are always stored on disk. If ofile = "" then the stage will not store the result on disk and will return nothing. It will however hold partial output results temporarily in memory. This is useful for stage that are only intermediate stage.

References

Dalponte, M. and Coomes, D. A. (2016), Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data. Methods Ecol Evol, 7: 1236–1245. doi:10.1111/2041-210X.12575.

Examples

f <- system.file("extdata", "MixedConifer.las", package="lasR")

reader <- reader_las(filter = keep_first())
chm <- rasterize(1, "max")
lmx <- local_maximum_raster(chm, 5)
tree <- region_growing(chm, lmx, max_cr = 10)
u <- exec(reader + chm + lmx + tree, on = f)

# terra::plot(u$rasterize)
# plot(u$local_maximum, add = T, pch = 19, cex = 0.5)
# terra::plot(u$region_growing, col = rainbow(150))
# plot(u$local_maximum, add = T, pch = 19, cex = 0.5)