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My original catalog:

enter image description here

has a mean density of 2.2 points/m2, but some areas have a higher density. :

> plot(lidR::grid_density(ctg, 1), main = "Density grid 1x1 m ", breaks = c(0,2,3,5,16), col = topo.colors(4))

enter image description here

I want to homogenize the point cloud to the maximum target density of 3 points/m2. To do so I use the function decimate_points with the algorithm homogenize:

ctg_thinned = decimate_points(ctg_clip, homogenize(density = 3, res = 25, use_pulse = FALSE))
> plot(lidR::grid_density(ctg_thinned , 1), breaks = c(0,2,3,5,16), col = topo.colors(4))

enter image description here

How is it possible that I get higher densities than 3 and even more, higher maximum densities than before?

Maybe is not the correct algortihm I am using. If not, how should I do I do it?

1 Answer 1

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Your catalog has overlapping tiles. This is a problem for processing because some regions appear twice or are loaded twice and therfore you processed some regions twice which explained why you have twice more point in the overlapping parts. You must retile you catalog to get non overlapping chunk when processing. Good new you can retile while decimating.

opt_chunk_size(ctg_clip) = 1000
opt_output_files(ctg_clip) = "/path/to/folder/{XCENTER}_{YCENTER}_homogeneized"
ctg_thinned = decimate_points(ctg_clip, homogenize(density = 3, res = 25, use_pulse = FALSE))

This way you are forcing lidR do create independent chunks of 1000 x 1000m that do not overlap. For each chunk you homogenize the density and you write the point cloud into a new file. This should do the job.

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