Error: Invalid data: ScanAngleRank is not an integer on 8 bits

[Robin-hartley]

Hi there JRR,

I've been working on a bit of Riegl MiniVUX data for the past 6 months, had a nice script running in LidR to derive some vegetation metrics etc, and then was unhappy with the noise in the data, so I created a pipeline in LASTools to denoise the data prior to entry into Lidr. Unfortunately, I am now getting this error message when I try to ground classify the data:

plan(multisession)
opt_output_files(ctg) <- paste0("D:/FILEDIRECTORY/{*}_gc")
ctg_gc <- classify_ground(ctg, csf())
#> Processing [>------------------------------------------------------]   1% (1/81) eta:  4m
#> Error: Invalid data: ScanAngleRank is not an integer on 8 bits

I assume this is something to do with the format of the ScanAngleRank data that is written to the LAS file by LASTools. The same happens when I export data from CloudCompare.

I have a small snippet of the data I am working with here - RH_test_data.zip

Are you able to reproduce this error, and is it a bug? Or do I need to somehow edit the LAS file? I saw a bit of code that looked potentially useful here: https://github.com/Jean-Romain/lidR/issues/319 in which you suggested changing the ScanAngleRank data to an integer:

las@data[["ScanAngleRank"]] <- as.integer(las@data[["ScanAngle"]]) # If prf >= 6

However, when I tried this on the test data I have provided, well, I couldn't load it into lidR as the same error appeared.

Thanks in advance,

RH

[Jean-Romain]

The issue is from rlas. I transfered the issue. The value -128 triggered a false positive error. Update rlas 1.5.1 from github.`You now have only warnings

 las = readLAS("~/Téléchargements/issue 454/RH_test_data.laz")
#> Warnings :
#> 1: Invalid data: ScanAngleRank greater than -90 degrees. 
#> 2: Invalid data: ScanAngleRank greater than 90 degrees 
#> 3: Invalid data: 66 points with a 'return number' greater than the 'number of returns'. 

[Robin-hartley]

Many thanks for getting to this so promptly