Using PDAL to classify isolated LiDAR points as noise

LiDAR data often contains noise and it is necessary to identify and/or remove them. An example of a LAS file containing noise in the form of low isolated points beneath the ground is shown in the screen shot below.

Isolated points can be easily identified by using statistical filtering methods, which the PDAL open source software has.

To filter out these points using PDAL, perform the following steps.

1. Open up the OSGeo4W Shell.
   
   The OSGeo4W Shell prompt appears.
2. In the prompt, type in the command:
   
   C:\> pdal translate -i in_noisy.las -o out_filtered.las outlier --filters.outlier.method="statistical" --filters.outlier.mean_k=8 --filters.outlier.multiplier=3.0 -v 4
   
   Note:
   -i in_noisy.las is the input LAS file
   -o out_filtered.las specifies the output LAS file
   outlier tells PDAL to apply the outlier filter
   --filters.outlier.**** options specify the various outlier parameters
   -v 4 indicates the processing messages verbosity level
   
   
3. After running the command, the isolated points are classified as Class 7 - Low Noise points in the output LAS file.
   
   The point cloud colored by classification.
   
   
   The resultant LAS file colored by elevation and with the class 7 - Low noise points turned off.