I'm encountering an issue while working with LAS data generated from the open-source software CloudCompare. I've exported 24 geometric features to a LAS file format(1.4), and I'm experiencing difficulties when trying to read this data.

Can you provide some insights or information regarding any limitations for LAS data with extra features?

After exporting the LAS file and attempting to import it into CloudCompare, all the saved features are successfully read. However, when I use the R LidR package's readLAS function, it doesn't seem to work as expected. It looks like, after the 9th feature, it cuts off the others.

Here's a snippet of the R code I'm using:


las_file <- "../data/CrossSection_20cm-features-all-2.las"
data <- readLAS(files = las_file)

Platform: x86_64-w64-mingw32/x64 (64-bit) R version 4.3.1 (2023-06-16 ucrt) LidR 4.0.4

1 Answer 1


The package rlas (which is actually the package that reads las/laz files) can only read up to 10 extra attributes. This is a kind of hard coded limit because you can select the attributes using one character with the filter argument such as filter = xyzi012 for X, Y, Z, Intensity and extra bytes attributes 0 to 2. Thus, you can't select attribute 10 because this means 1 and 0. If you want to read more, you can open a feature request in the rlas repos.

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