Quickstart#
Introduction#
The quickest way to start using PDAL is to leverage builds that were constructed by the PDAL development team using Conda.
Directly from the Conda front page,
Conda is an open source package management system and environment management system that runs on Windows, macOS and Linux. Conda quickly installs, runs and updates packages and their dependencies. Conda easily creates, saves, loads and switches between environments on your local computer.
This exercise will print the first point of an ASPRS LAS file. It will utilize the PDAL command line application to inspect the file.
Note
If you need to compile your own copy of PDAL, see Compilation for more details.
Install Conda#
Conda installation instructions can be found at the following links. Read through them a bit for your platform so you have an idea what to expect.
Note
We will assume you are running on Windows, but the same commands should work in macOS or Linux too – though definition of file paths might provide a significant difference.
Run Conda#
On macOS and Linux, all Conda commands are typed into a terminal window. On Windows, commands are typed into the Anaconda Prompt window. Instructions can be found in the Conda Getting Started guide.
Test Installation#
To test your installation, simply run the command conda list from your
terminal window or the Anaconda Prompt. A list of installed packages should
appear.
Install the PDAL Package#
A PDAL package based on the latest release, including all recent patches, is pushed to the conda-forge channel on anaconda.org with every code change on the PDAL maintenance branch.
Warning
It is a good idea to install PDAL in it’s own environment (or
add it to an existing one). You will NOT want to add it to your default
environment named base. Managing environments is beyond the scope of
the quickstart, but you can read more about it here.
To install the PDAL package so that we can use it to run PDAL commands, we run
the following command to create an environment named myenv, installing PDAL
from the conda-forge channel.
conda create --yes --name myenv --channel conda-forge pdal
Depending on what packages you may or may not have already installed, the output should look something like:
Solving environment: done
## Package Plan ##
environment location: C:\Miniconda3\envs\myenv
added / updated specs:
- pdal
The following packages will be downloaded:
package | build
---------------------------|-----------------
pdal-1.7.2 | py35h33f895e_1 8.6 MB conda-forge
setuptools-39.2.0 | py35_0 591 KB conda-forge
numpy-1.14.3 | py35h9fa60d3_2 42 KB
------------------------------------------------------------
Total: 9.2 MB
The following NEW packages will be INSTALLED:
boost: 1.66.0-py35_vc14_1 conda-forge [vc14]
boost-cpp: 1.66.0-vc14_1 conda-forge [vc14]
ca-certificates: 2018.4.16-0 conda-forge
cairo: 1.14.10-vc14_0 conda-forge [vc14]
certifi: 2018.4.16-py35_0 conda-forge
curl: 7.60.0-vc14_0 conda-forge [vc14]
expat: 2.2.5-vc14_0 conda-forge [vc14]
flann: 1.9.1-h0953f56_2 conda-forge
freexl: 1.0.5-vc14_0 conda-forge [vc14]
geotiff: 1.4.2-vc14_1 conda-forge [vc14]
hdf4: 4.2.13-vc14_0 conda-forge [vc14]
hdf5: 1.10.1-vc14_2 conda-forge [vc14]
hexer: 1.4.0-vc14_1 conda-forge [vc14]
icc_rt: 2017.0.4-h97af966_0
icu: 58.2-vc14_0 conda-forge [vc14]
intel-openmp: 2018.0.3-0
jpeg: 9b-vc14_2 conda-forge [vc14]
kealib: 1.4.7-vc14_4 conda-forge [vc14]
krb5: 1.14.6-vc14_0 conda-forge [vc14]
laszip: 3.2.2-vc14_0 conda-forge [vc14]
laz-perf: 1.2.0-vc14_1 conda-forge [vc14]
libgdal: 2.2.4-vc14_4 conda-forge [vc14]
libiconv: 1.15-vc14_0 conda-forge [vc14]
libnetcdf: 4.6.1-vc14_2 conda-forge [vc14]
libpng: 1.6.34-vc14_0 conda-forge [vc14]
libpq: 9.6.3-vc14_0 conda-forge [vc14]
libspatialite: 4.3.0a-vc14_19 conda-forge [vc14]
libssh2: 1.8.0-vc14_2 conda-forge [vc14]
libtiff: 4.0.9-vc14_0 conda-forge [vc14]
libxml2: 2.9.8-vc14_0 conda-forge [vc14]
libxslt: 1.1.32-vc14_0 conda-forge [vc14]
mkl: 2018.0.3-1
mkl_fft: 1.0.2-py35_0 conda-forge
mkl_random: 1.0.1-py35_0 conda-forge
nitro: 2.7.dev2-vc14_0 conda-forge [vc14]
numpy: 1.14.3-py35h9fa60d3_2
numpy-base: 1.14.3-py35h5c71026_0
openjpeg: 2.3.0-vc14_2 conda-forge [vc14]
openssl: 1.0.2o-vc14_0 conda-forge [vc14]
pcl: 1.8.1-hd76163c_1 conda-forge
pdal: 1.7.2-py35h33f895e_1 conda-forge
pip: 9.0.3-py35_0 conda-forge
pixman: 0.34.0-vc14_2 conda-forge [vc14]
postgresql: 10.3-py35_vc14_0 conda-forge [vc14]
proj4: 4.9.3-vc14_5 conda-forge [vc14]
python: 3.5.5-1 conda-forge
setuptools: 39.2.0-py35_0 conda-forge
sqlite: 3.20.1-vc14_2 conda-forge [vc14]
tiledb: 1.4.1 conda-forge
vc: 14-0 conda-forge
vs2015_runtime: 14.0.25420-0 conda-forge
wheel: 0.31.0-py35_0 conda-forge
wincertstore: 0.2-py35_0 conda-forge
xerces-c: 3.2.0-vc14_0 conda-forge [vc14]
xz: 5.2.3-0 conda-forge
zlib: 1.2.11-vc14_0 conda-forge [vc14]
Downloading and Extracting Packages
pdal-1.7.2 | 8.6 MB | ###################################### | 100%
setuptools-39.2.0 | 591 KB | ###################################### | 100%
numpy-1.14.3 | 42 KB | ###################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate myenv
#
# To deactivate an active environment, use
#
# $ conda deactivate
Note
PDAL’s Python extension is managed separately from the PDAL package. To
install it, replace pdal with python-pdal in any of the commands in
this section. Seeing as how PDAL is a dependency of the Python extension,
you will actually get two for the price of one!
To install PDAL to an existing environment names myenv, we would run the
following command.
conda install --name myenv --channel conda-forge pdal
Finally, to update PDAL to the latest version, run the following.
conda update pdal
Experimental Install via Pixi#
Pixi is a fast software package manager built on top of Conda/Mamba that spins up development environments quickly on Windows, macOS and Linux.
Prerequisites#
Detailed installation instructions can be found here, but one of the following commands should work depending on your OS.
curl -fsSL https://pixi.sh/install.sh | bash
Powershell:
iwr -useb https://pixi.sh/install.ps1 | iex
winget:
winget install prefix-dev.pixi
Install Pixi Environment#
After Pixi is installed, you can run
git clone https://github.com/PDAL/PDAL.git
cd PDAL
pixi shell
This will fetch the latest PDAL code, install all environment dependencies and then activate a supercharged environment that we lovingly call goldendoodle. From now on, each time you want to run PDAL in a new shell, you have to navigate to the PDAL folder and run pixi shell again.
Go ahead and test that PDAL is installed!
pdal --version
--------------------------------------------------------------------------------
pdal 2.8.2 (git-version: Release)
--------------------------------------------------------------------------------
Fetch Sample Data#
We need some sample data to play with, so we’re going to download the
autzen.laz file. Inside your terminal (assuming Windows), issue the
following command:
explorer.exe https://github.com/PDAL/data/raw/master/autzen/autzen.laz
In the download dialog, save the file to your Downloads folder, e.g.,
C:\Users\hobu\Downloads.
Print the first point#
To print the first point only, issue the following command (replacing of course
hobu with your user name, or another path altogether, depending on where
you saved the file).
pdal info C:\Users\hobu\Downloads\autzen.laz -p 0
Here’s a summary of what’s going on with that command invocation
pdal: We’re going to run thepdalcommand.info: We want to run info on the data.autzen.laz: Theautzen.lazfile that we want information from.
Warning 1: Cannot find datum.csv or gdal_datum.csv
Warning 1: Cannot find ellipsoid.csv
{
"filename": "C:\\Users\\hobu\\Downloads\\autzen.laz",
"pdal_version": "1.7.2 (git-version: Release)",
"points":
{
"point":
{
"Blue": 93,
"Classification": 1,
"EdgeOfFlightLine": 0,
"GpsTime": 245379.3984,
"Green": 102,
"Intensity": 4,
"NumberOfReturns": 1,
"PointId": 0,
"PointSourceId": 7326,
"Red": 84,
"ReturnNumber": 1,
"ScanAngleRank": -17,
"ScanDirectionFlag": 0,
"UserData": 128,
"X": 637177.98,
"Y": 849393.95,
"Z": 411.19
}
}
}
What’s next?#
Visit Applications to find out how to utilize PDAL applications to process data on the command line yourself.
Visit Development to learn how to embed and use PDAL in your own applications.
Readers lists the formats that PDAL can read, Filters lists the kinds of operations you can do with PDAL, and Writers lists the formats PDAL can write.
Tutorials contains a number of walk-through tutorials for achieving many tasks with PDAL.
The PDAL workshop contains numerous hands-on examples with screenshots and example data of how to use PDAL Applications to tackle point cloud data processing tasks.
Python describes how PDAL embeds and extends Python and how you can leverage these capabilities in your own programs.
See also
Community is a good source to reach out to when you’re stuck.