I am studying the foliage density of forest plots below 2 metres in height using mobile terrestrial laser scanning. I want to filter out the tree stems from the point clouds so that the point density estimates do not include them. I have been using the lidR and TreeLS packages to process my point clouds. So far I have normalized the clouds and classified the tree stems using example code given in the TreeLS package documentation:

tls1 = readTLS("tls1.las") %>%
tlsNormalize %>%
map = treeMap(tls1, map.hough())
tls2 = treePoints(tls1, map, trp.crop(circle=FALSE))
tls3 = stemPoints(tls2, stm.hough(pixel_size = 0.03))

This successfully identifies the tree stems.

To filter the stems out, I have tried using the filter_poi() function:

tls4 <- filter_poi(tls3, Stem = "FALSE")

There is a column in the point cloud dataset entitled "Stem" with TRUE/FALSE values so I thought this would work, but I get this error:

Error in lasfilter_(las, lazyeval::dots_capture(...)) : 
  `conditions` must be logical.
  • 3
    It is just incorrect R syntax. Use filter_poi(tls3, Stem == FALSE)
    – JRR
    Oct 16, 2020 at 16:41
  • Thanks JRR that works without an error. However, when I then plot the scan before and after filtering the stem points, there is no change in the image. When I look for unique values in the Stem column "TRUE" has been removed, so the filtering has worked. There must be a problem with the stem classification?
    – Amy
    Oct 20, 2020 at 11:08
  • Are you sure the stems were properly segmented initially in tls3? If not it is no longer a lidR question. Can't help.
    – JRR
    Oct 20, 2020 at 11:45

1 Answer 1


Try classifying the stems in the 'Classification' column after calling stemPoints.

I've used the following code to classify and then filter stems:


tls@data[Stem == T, Classification := 20] 

then filter

stems  = filter_poi(tls, Classification == 20L)

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