Next create a pipeline.txt for pdal with the classification (For DSM, 1 are unclassified points like buildings and treetops, while 2 are ground points, if you want a DEM, you can also make them this way too with Classification of 2:2):
Next convert the point clouds into digital surface model (GeoTIFF), you can use this shell command with xargs to go over each LAS file, using the above pipeline:
The above command can be somewhat slow depending on how many LAZ point clouds you need to go through and your selected resolution. -P3 sets the number of parallel process (3) which can help speed things up a bit.
Now we have the digital surface models raster that can be used in QGIS for hillshade for 3D.
Build a virtual raster (dsm.vrt) for easy loading into QGIS rather than loading separate files.
People were asking how I was extracting the digital terrain model (tree/building elevation) from the NYS GIS LiDAR point clouds (LAS) files. While the digital surface models (bare earth) models are widely available in raster digital elevation model GeoTIFF, these files are bare earth and donโt include vegetation or buildings. But you can easily create raster digital elevation model GeoTIFF from the LIDAR point clouds with the PDAL โ Point Data Abstraction Library.
Install PDAL
Itโs easy if you are running Ubuntu Linux โ itโs in standard distribution with 20.04 LTS or later. Most modern distributions of Linux include it in their repositories.
sudo apt install pdal
Download LiDAR Point Clouds
You can download the individual cloud files from NYS GIS FTP site. You can use the LiDAR Shapefile indexes on that website to figure out which file you need. Be aware you may have to download and store a significant amount of data โ each roughly 556 acre tile (less then a square mile) is between 500 and 1,000 MB. So you will want to do this somewhere you have a lot of free unlimited data service and storage on your hard drive. And patience while it downloads.
Extract the Digital Terrain Model
You should create a text file called pdal_dtm.json or something similar. The text file should contain:
This creates the pdal โpipelineโ configuration file for the conversion. An explanation of important lines you will need to change:
โ18TWN220520.lasโ โ Input point cloud LAS file โtypeโ: โfilters.rangeโ โ Tells PDAL to filter points based on request โlimitsโ: โClassification[1:1]โ โ Layer to extract * โfilenameโ:โdsm.tifโ โ Export file name โgdaldriverโ:โGTiffโ โ Use GeoTIFF export (same as standard DEM files) โresolutionโ: 0.5 โ Resolution in meters for export, typically 0.5m or 1m depending on survey โoutput_typeโ: โmaxโ โ Highest point reflected back within that point, to get digital surface elevation. You can also use min/max/mean/count/stdev/idw. โtypeโ:โwriters.gdalโ โ Use the GDAL library for create GeoTIFF
* Layers in NYS GIS Point Clouds โ โThese point clouds will have at a minimum 2 classifications; Class 1 Unclassified, and Class 2 Bare Earth.โ Layer 1 is the digital surface model, it contains building heights and tree/crop cover. Layer 2 โBare Earthโ is the same as what you get from the LiDAR Digital Elevation GeoTIFFs that are widely available on NYSGIS website. Be aware that the Class 2 points may have no-data areas, where no ground elevation was detected due to tree cover or other things blocking ground. The DEM files you download from NYSGIS have these areas filled in with interpolation from surrounding areas.
Once your configuration file is done, run the command:
pdal pipeline pdal_dtm.json
As the Point Cloud files are internally indexed, the export should take only a matter of seconds on a modern desktop computer. The exported DEM/GeoTIFF file will be between 15 to 25 MB, which is much smaller then the point cloud. Then you can load in Quantum GIS or your favorite non-free software GIS client like any other Raster DEM file.
To calculate the building or tree height, just subtract the Class 1 raster from Class 2 raster, using the Raster Calculator in QGIS or your favorite GIS program. Or better yet, subtract Class 1 points from the already processed DEM files on NYSGIS website, as they have the missing bare earth data filled in.
Generally speaking, north sloping property is considered less valuable due to being colder with less sunlight, which is bad for agriculture, solar production and general human happiness.
Towns in the Eastern Adirondacks and Eastern Catskills have the greatest change in elevation in their borders. This is done with 100 meter digital elevation model, so this does not include peaks -- but a comparison of general height of land in one part of the town compared to another.