::
:: a batch script for converting a few raw flight lines into a
:: number of products (due to memory limitations the workflow
:: shown below only works for smaller projects with maximal 20
:: million points)
::

:: include LAStools in PATH to allow running script from here

set PATH=%PATH%;..;

:: use lasground to find the bare-earth points in an on-the-fly
:: merge of the flight strips with the standard '-city' granularity 
:: (which uses a step of 25 meter) and '-extra_fine' setting for
:: the initial ground estimate (see: lasground_README.txt). the 
:: '-files_are_flightlines' flag assures that information about
:: which point is from which flight line is preserved. the merged
:: and ground-classified result is output to a compressed file.

lasground -i strips_raw\*.laz -merged -files_are_flightlines ^
          -city -ultra_fine ^
          -o ground.laz

:: NOTE: if the only objective is to create a bare-earth DTM rasters
:: (as it may well be the case in archeological applications) then we
:: could stop here

:: use lasheight to remove low and high outliers that are often
:: just noise (e.g. clouds or birds). by default lasheight uses
:: the points classified as ground to construct a TIN and then
:: calculates the height of all other points in respect to this
:: ground surface TIN. with '-drop_above 50 -drop_below -5' all
:: points that are 50 meters above the ground or 5 meters below
:: the ground are removed from the output LAZ file.

lasheight -i ground.laz ^
          -drop_above 50 -drop_below -5 ^
          -o denoised.laz

:: recompute a tighter bounding box

lasinfo -i denoised.laz -repair_bb

:: use lasclassify to identify buildings and trees in the denoised
:: files. your milage may vary on this step because automatic LiDAR
:: classification is a hard problem. all the default settings are
:: used (see: lasclassify_README.txt).

lasclassify -i denoised.laz ^
            -o classified.laz