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I have unclassified Terrestrial Laser Scanning (TLS) point cloud data which has some noise. Is there a function in the lidR package which can be used to remove noise?

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Short answer: No. And more specifically lidR is designed for ALS primarily, if ever I add a function for noise removal it will be for ALS first.

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    Thanks @JRR, I found lidR has very good functions which can be used for extracting forest metrics from ALS data. Can they be used for TLS point clouds as well? Do you have any suggestions on effectively using it to TLS data? – Sher Feb 26 at 6:19
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It depends on what is your purpose. If you are looking for a very high resolution forest analysis may be that noise means something and must be analyzed in a particular way. If you just want to "simplify" (decimation) your data and get an homogenized distribution of points you can use the following functions (here is the complete guide):

library(lidR)
las <- readLAS(file)

#option 1 - homogenized las with density = 1 and res = 5
s1 <- lasfilterdecimate(las, homogenize(1,5))

#option 2 - get highest points in 5m resolution
s2 <- lasfilterdecimate(las, highest(5))

#option 3 - get random points in 5m resolution
s3 <- lasfilterdecimate(las, random(5))
  • Thanks @César Arquero. Point cloud has weird scan error, contains thousands of noise points under ground and above ground. Therefore these tools may not be suitable for my case – Sher Mar 5 at 3:45

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