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<li class="toctree-l2"><a class="reference internal" href="#what-is-pdal">What is PDAL?</a></li>
<li class="toctree-l2"><a class="reference internal" href="#what-is-its-big-idea">What is its big idea?</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#why-would-you-want-to-do-that">Why would you want to do that?</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#how-is-it-different-than-other-tools">How is it different than other tools?</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#lastools">LAStools</a></li>
<li class="toctree-l3"><a class="reference internal" href="#pcl">PCL</a></li>
<li class="toctree-l3"><a class="reference internal" href="#greyhound-and-entwine">Greyhound and Entwine</a></li>
<li class="toctree-l3"><a class="reference internal" href="#plas-io-and-potree">plas.io and Potree</a></li>
<li class="toctree-l3"><a class="reference internal" href="#others">Others</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#where-did-pdal-come-from">Where did PDAL come from?</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#how-is-point-cloud-data-different-than-raster-or-vector-geo-data">How is point cloud data different than raster or vector geo data?</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#what-tasks-are-pdal-good-at">What tasks are PDAL good at?</a></li>
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<div class="section" id="about">
<span id="id1"></span><h1>About<a class="headerlink" href="#about" title="Permalink to this headline">¶</a></h1>
<div class="section" id="what-is-pdal">
<h2>What is PDAL?<a class="headerlink" href="#what-is-pdal" title="Permalink to this headline">¶</a></h2>
<p><a class="reference external" href="https://pdal.io/">PDAL</a> is Point Data Abstraction Library. It is a C/C++ open source library
and applications for translating and processing <a class="reference external" href="https://en.wikipedia.org/wiki/Point_cloud">point cloud data</a>. It is not
limited to <a class="reference external" href="https://en.wikipedia.org/wiki/Lidar">LiDAR</a> data, although the focus and impetus for many of the
tools in the library have their origins in LiDAR.</p>
</div>
<div class="section" id="what-is-its-big-idea">
<h2>What is its big idea?<a class="headerlink" href="#what-is-its-big-idea" title="Permalink to this headline">¶</a></h2>
<p>PDAL allows you to compose <a class="reference internal" href="stages/filters.html#filters"><span class="std std-ref">operations</span></a> on point clouds into
<a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">pipelines</span></a> of <a class="reference internal" href="stages/index.html#stage-index"><span class="std std-ref">stages</span></a>. These pipelines can
be written in a declarative JSON syntax or constructed using the available API.</p>
<div class="section" id="why-would-you-want-to-do-that">
<h3>Why would you want to do that?<a class="headerlink" href="#why-would-you-want-to-do-that" title="Permalink to this headline">¶</a></h3>
<p>A task might be to load some <a class="reference external" href="http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html">ASPRS LAS</a> (the most common LiDAR binary format)
data into a database, but you wanted to transform it into a common coordinate
system along the way.</p>
<p>One option would be to write a specialized monolithic
program that reads LAS data, reprojects it as necessary, and then handles the
necessary operations to insert the data in the appropriate format in the
database. This approach has a distinct disadvantage in that without careful
planning it could quickly spiral out of control as you add new little tweaks
and features to the operation. It ends up being very specific, and it
does not allow you to easily reuse the component that reads the LAS data
separately from the component that transforms the data.</p>
<p>The PDAL approach is to chain together a set of components,
each of which encapsulates specific functionality. The components allow for
reuse, composition, and separation of concerns. PDAL views point cloud
processing operations as a pipeline composed as a series of stages. You might
have a simple pipeline composed of a <a class="reference internal" href="stages/readers.las.html#readers-las"><span class="std std-ref">LAS Reader</span></a> stage, a
<a class="reference internal" href="stages/filters.reprojection.html#filters-reprojection"><span class="std std-ref">Reprojection</span></a> stage, and a <a class="reference internal" href="stages/writers.pgpointcloud.html#writers-pgpointcloud"><span class="std std-ref">PostgreSQL Writer</span></a>, for example. Rather than writing a single, monolithic
specialized program to perform this operation, you can dynamically compose it
as a sequence of steps or operations.</p>
<div class="figure" id="id4">
<img alt="_images/las-reproject-pgpointcloud.png" src="_images/las-reproject-pgpointcloud.png" />
<p class="caption"><span class="caption-text">A simple PDAL pipeline composed of a reader, filter, and writer
stages.</span></p>
</div>
<p>A PDAL JSON <a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">Pipeline</span></a> that composes this operation to reproject
and load the data into PostgreSQL might look something like the following:</p>
<div class="highlight-json"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18</pre></div></td><td class="code"><div class="highlight"><pre><span></span><span class="p">{</span>
<span class="nt">"pipeline"</span><span class="p">:[</span>
<span class="p">{</span>
<span class="hll"> <span class="nt">"type"</span><span class="p">:</span><span class="s2">"readers.las"</span><span class="p">,</span>
</span> <span class="nt">"filename"</span><span class="p">:</span><span class="s2">"input.las"</span>
<span class="p">},</span>
<span class="p">{</span>
<span class="hll"> <span class="nt">"type"</span><span class="p">:</span><span class="s2">"filters.reprojection"</span><span class="p">,</span>
</span> <span class="nt">"out_srs"</span><span class="p">:</span><span class="s2">"EPSG:3857"</span>
<span class="p">},</span>
<span class="p">{</span>
<span class="hll"> <span class="nt">"type"</span><span class="p">:</span><span class="s2">"writers.pgpointcloud"</span><span class="p">,</span>
</span> <span class="nt">"connection"</span><span class="p">:</span><span class="s2">"host='localhost' dbname='lidar' user='hobu'"</span><span class="p">,</span>
<span class="nt">"table"</span><span class="p">:</span><span class="s2">"output"</span><span class="p">,</span>
<span class="nt">"srid"</span><span class="p">:</span><span class="s2">"3857"</span>
<span class="p">}</span>
<span class="p">]</span>
<span class="p">}</span>
</pre></div>
</td></tr></table></div>
<p>PDAL can compose intermediate stages for operations such as filtering,
clipping, tiling, transforming into a processing pipeline and reuse as
necessary. It allows you to define these pipelines as <a class="reference external" href="https://en.wikipedia.org/wiki/JSON">JSON</a>, and it
provides a command, <a class="reference internal" href="apps/pipeline.html#pipeline-command"><span class="std std-ref">pipeline</span></a>, to allow you to execute them.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Raster processing tools often compose operations with this approach.
PDAL conceptually steals its pipeline modeling from <a class="reference external" href="http://gdal.org/">GDAL</a>’s
<a class="reference external" href="http://www.gdal.org/gdal_vrttut.html">Virtual Raster Format</a>.</p>
</div>
</div>
</div>
<div class="section" id="how-is-it-different-than-other-tools">
<h2>How is it different than other tools?<a class="headerlink" href="#how-is-it-different-than-other-tools" title="Permalink to this headline">¶</a></h2>
<div class="section" id="lastools">
<h3>LAStools<a class="headerlink" href="#lastools" title="Permalink to this headline">¶</a></h3>
<p id="index-0">One of the most common open source processing tool suites available for LiDAR
processing is <a class="reference external" href="http://lastools.org">LAStools</a> from <a class="reference external" href="https://www.cs.unc.edu/~isenburg/">Martin Isenburg</a>. PDAL is different in
philosophy in a number of important ways:</p>
<ol class="arabic simple">
<li>All components of PDAL are released as open source software under an
<a class="reference external" href="https://opensource.org/licenses">OSI</a>-approved license.</li>
<li>PDAL allows application developers to provide proprietary extensions that
act as stages in processing pipelines. These might be things like custom
format
readers, specialized exploitation algorithms, or entire processing pipelines.</li>
<li>PDAL can operate on point cloud data of any format
– not just <a class="reference external" href="http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html">ASPRS LAS</a>. <a class="reference external" href="http://lastools.org">LAStools</a> can read and write formats other than
LAS, but relates all data to its internal handling of LAS data, limiting
it to <a class="reference internal" href="dimensions.html#dimensions"><span class="std std-ref">dimension</span></a> types provided by the LAS format.</li>
<li>PDAL is coordinated by users with its declarative <a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">JSON</span></a>
syntax. LAStools is coordinated by linking lots of small, specialized
command line utilities together with intricate arguments.</li>
<li>PDAL is an open source project, with all of its development activites
available online at <a class="reference external" href="https://github.com/PDAL/PDAL">https://github.com/PDAL/PDAL</a></li>
</ol>
</div>
<div class="section" id="pcl">
<span id="about-pcl"></span><h3>PCL<a class="headerlink" href="#pcl" title="Permalink to this headline">¶</a></h3>
<p id="index-1"><a class="reference external" href="http://pointclouds.org">PCL</a> is a complementary, rather than substitute, open source software
processing suite for point cloud data. The developer community of the PCL
library is focused on algorithm development, robotic and computer vision, and
real-time laser scanner processing. PDAL links and uses PCL, and PDAL provides
a convenient pipeline mechanism to orchestrate PCL operations.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">See <a class="reference internal" href="tutorial/pcl_block_tutorial.html#pcl-block-tutorial"><span class="std std-ref">Filtering data with PCL</span></a> for more detail on how to take advantage of
PCL capabilities within PDAL operations.</p>
</div>
</div>
<div class="section" id="greyhound-and-entwine">
<h3>Greyhound and Entwine<a class="headerlink" href="#greyhound-and-entwine" title="Permalink to this headline">¶</a></h3>
<p id="index-2"><a class="reference external" href="http://greyhound.io">Greyhound</a> is an open source software from <a class="reference external" href="https://hobu.co">Hobu, Inc.</a> that allows clients
to query and stream progressive point cloud data over the network. <a class="reference external" href="https://entwine.io">Entwine</a>
is open source software from Hobu, Inc. that organizes massive point cloud
collections into <a class="reference external" href="http://greyhound.io">Greyhound</a>-streamable data services. These two software
projects allow province-scale LiDAR collections to be organized and served
via HTTP clients over the internet. PDAL provides <a class="reference internal" href="stages/readers.greyhound.html#readers-greyhound"><span class="std std-ref">readers.greyhound</span></a> to
allow users to read data into PDAL processes from that server.</p>
</div>
<div class="section" id="plas-io-and-potree">
<h3>plas.io and Potree<a class="headerlink" href="#plas-io-and-potree" title="Permalink to this headline">¶</a></h3>
<p><a class="reference external" href="http://plas.io">plas.io</a> is a <a class="reference external" href="https://en.wikipedia.org/wiki/WebGL">WebGL</a> HTML5 point cloud renderer that speaks <a class="reference external" href="http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html">ASPRS LAS</a> and
<a class="reference external" href="http://laszip.org">LASzip</a> compressed LAS. You can find the software for it at plasiojs.io and
<a class="reference external" href="https://github.com/hobu/plasio-ui">https://github.com/hobu/plasio-ui</a></p>
<p><a class="reference external" href="http://potree.org">Potree</a> is a <a class="reference external" href="https://en.wikipedia.org/wiki/WebGL">WebGL</a> HTML5 point cloud renderer that speaks <a class="reference external" href="http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html">ASPRS LAS</a> and
<a class="reference external" href="http://laszip.org">LASzip</a> compressed LAS. You can find the software at
<a class="reference external" href="https://github.com/potree/potree/">https://github.com/potree/potree/</a></p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Both renderers can now consume data from Greyhound. See them in action at
<a class="reference external" href="http://speck.ly">http://speck.ly</a> and <a class="reference external" href="http://potree.entwine.io">http://potree.entwine.io</a></p>
</div>
</div>
<div class="section" id="others">
<h3>Others<a class="headerlink" href="#others" title="Permalink to this headline">¶</a></h3>
<p id="index-3">Other open source point cloud softwares tend to be Desktop GUI, rather than
library, focused. They include some processing operations, and sometimes they
even embed tools such as PDAL. We’re obviously biased toward PDAL, but you
might find useful bits of functionality in them. These other tools include:</p>
<ul class="simple">
<li><a class="reference external" href="http://liblas.org">libLAS</a></li>
<li><a class="reference external" href="http://www.danielgm.net/cc/">CloudCompare</a></li>
<li><a class="reference external" href="http://www.idaholidar.org/tools/fusion-ldv/">Fusion</a></li>
<li><a class="reference external" href="https://www.orfeo-toolbox.org/">OrfeoToolbox</a></li>
</ul>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">The <a class="reference external" href="http://liblas.org">libLAS</a> project is an open source project that pre-dates PDAL, and
provides some of the processing capabilities provided by PDAL. It is
currently in maintenance mode due to its dependence on LAS, the release of
relevant LAStools capabilities as open source, and the completion of
<a class="reference external" href="https://pypi.python.org/pypi/laspy/1.4.1">Python LAS</a> software.</p>
</div>
</div>
</div>
<div class="section" id="where-did-pdal-come-from">
<h2>Where did PDAL come from?<a class="headerlink" href="#where-did-pdal-come-from" title="Permalink to this headline">¶</a></h2>
<p>PDAL takes its cue from another very popular open source project – <a class="reference external" href="http://gdal.org/">GDAL</a>.
GDAL is Geospatial Data Abstraction Library, and it is used throughout the geospatial
software industry to provide translation and processing support for a variety
of raster and vector formats. PDAL provides the same capability for point
cloud data types.</p>
<p>PDAL evolved out of the development of database storage and access capabilities
for the U.S. Army Corps of Engineers <a class="reference external" href="http://www.erdc.usace.army.mil/Media/Fact-Sheets/Fact-Sheet-Article-View/Article/476649/remote-sensinggeographic-information-systems-center/">CRREL</a> <a class="reference external" href="http://lidar.io/">GRiD</a> project. Functionality that was creeping into <a class="reference external" href="http://liblas.org/">libLAS</a>
was pulled into a new library, and it was designed from the ground up to mimic
successful extract, transform, and load libraries in the geospatial software
domain. PDAL has steadily attracted more contributors as other software developers
use it to provide point cloud data translation and processing capability to
their software.</p>
<div class="section" id="how-is-point-cloud-data-different-than-raster-or-vector-geo-data">
<h3>How is point cloud data different than raster or vector geo data?<a class="headerlink" href="#how-is-point-cloud-data-different-than-raster-or-vector-geo-data" title="Permalink to this headline">¶</a></h3>
<p>Point cloud data are indeed very much like the typical vector point data type
of which many geospatial practitioners are familiar, but their volume causes some
significant challenges. Besides their <cite>X</cite>, <cite>Y</cite>, and <cite>Z</cite> locations, each point
often has full attribute information of other things like <cite>Intensity</cite>, <cite>Time</cite>,
<cite>Red</cite>, <cite>Green</cite>, and <cite>Blue</cite>.</p>
<p>Typical vector coverages of point data might max out at a million or so
features. Point clouds quickly get into the billions and even trillions, and
because of this specialized processing and management techniques must be used
to handle so much data efficiently.</p>
<p>The algorithms used to extract and exploit point cloud data are also significantly
different than typical vector GIS work flows, and data organization is extremely
important to be able to efficiently leverage the available computing. These
characteristics demand a library oriented toward these approaches and PDAL
achieves it.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Possible point cloud dimension types provided and supported by PDAL
can be found at <a class="reference internal" href="dimensions.html#dimensions"><span class="std std-ref">Dimensions</span></a>.</p>
</div>
</div>
</div>
<div class="section" id="what-tasks-are-pdal-good-at">
<h2>What tasks are PDAL good at?<a class="headerlink" href="#what-tasks-are-pdal-good-at" title="Permalink to this headline">¶</a></h2>
<p>PDAL is great at point cloud data translation work flows. It allows users to
apply algorithms to data by providing an abstract API to the content – freeing
users from worrying about many data format issues. PDAL’s format-free worry
does come with a bit of overhead cost. In most cases this is not significant,
but for specific processing work flows with specific data, specialized tools
will certainly outperform it.</p>
<p>In exchange for possible performance penalty or data model impedance, developers
get the freedom to access data over an abstract API, a multitude of algorithms
to apply to data within easy reach, and the most complete set of
point cloud format drivers in the industry. PDAL also provides a straightforward
command line, and it extends simple generic Python processing through Numpy. These
features make it attractive to software developers, data managers, and
scientists.</p>
</div>
<div class="section" id="what-are-pdal-s-weak-points">
<h2>What are PDAL’s weak points?<a class="headerlink" href="#what-are-pdal-s-weak-points" title="Permalink to this headline">¶</a></h2>
<p>PDAL doesn’t provide a friendly GUI interface, it expects that you have the
confidence to dig into the options of <a class="reference internal" href="stages/filters.html#filters"><span class="std std-ref">Filters</span></a>, <a class="reference internal" href="stages/readers.html#readers"><span class="std std-ref">Readers</span></a>, and
<a class="reference internal" href="stages/writers.html#writers"><span class="std std-ref">Writers</span></a>. We sometimes forget that you don’t always want to read source
code to figure out how things work. PDAL is an open source project in active
development, and because of that, we’re always working to improve it. Please
visit <a class="reference internal" href="community.html#community"><span class="std std-ref">Community</span></a> to find out how you can participate if you are
interested. The project is always looking for contribution, and the mailing
list is the place to ask for help if you are stuck.</p>
</div>
<div class="section" id="high-level-overview">
<h2>High Level Overview<a class="headerlink" href="#high-level-overview" title="Permalink to this headline">¶</a></h2>
<p>PDAL is first and foremost a software library. A successful software library
must meet the needs of software developers who use it to provide its software
capabilities to their own software. In addition to its use as a software
library, PDAL provides some <a class="reference internal" href="apps/index.html#apps"><span class="std std-ref">command line applications</span></a> users can
leverage to conveniently translate, filter, and process data with PDAL.
Finally, PDAL provides <a class="reference external" href="http://python.org/">Python</a> support in the form of embedded operations
and Python extensions.</p>
<div class="section" id="core-c-software-library">
<h3>Core C++ Software Library<a class="headerlink" href="#core-c-software-library" title="Permalink to this headline">¶</a></h3>
<p>PDAL provides a <a class="reference internal" href="api/index.html#api"><span class="std std-ref">C++ API</span></a> software developers can use to provide
point cloud processing capabilities in their own software. PDAL is
cross-platform C++, and it can compile and run on Linux, OS X, and Windows. The
best place to learn how to use PDAL’s C++ API is the <a class="reference internal" href="development/testing.html#pdal-test"><span class="std std-ref">test suite</span></a> and its <a class="reference external" href="https://github.com/PDAL/PDAL/tree/master/test/unit">source code</a>.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last">PDAL <a class="reference internal" href="tutorial/reading.html#reading"><span class="std std-ref">software</span></a> <a class="reference internal" href="development/writing.html#writing"><span class="std std-ref">development</span></a>
<a class="reference internal" href="development/writing-reader.html#writing-reader"><span class="std std-ref">tutorials</span></a> have more information on how to
use the library from a software developer’s perspective.</p>
</div>
</div>
<div class="section" id="command-line-utilities">
<h3>Command Line Utilities<a class="headerlink" href="#command-line-utilities" title="Permalink to this headline">¶</a></h3>
<p id="index-4">PDAL provides a number of <a class="reference internal" href="apps/index.html#apps"><span class="std std-ref">applications</span></a> that allow users to
coordinate and construct point cloud processing work flows. Some key tasks
users can achieve with these applications include:</p>
<ul class="simple">
<li>Print <a class="reference internal" href="apps/info.html#info-command"><span class="std std-ref">info</span></a> about a data set</li>
<li>Data <a class="reference internal" href="apps/translate.html#translate-command"><span class="std std-ref">translation</span></a> from one point cloud format to
another</li>
<li>Application of exploitation algorithms<ul>
<li>Generate a DTM</li>
<li>Remove noise</li>
<li>Reproject from one coordinate system to another</li>
<li>Classify points as <a class="reference internal" href="apps/ground.html#ground-command"><span class="std std-ref">ground/not ground</span></a></li>
</ul>
</li>
<li><a class="reference internal" href="apps/merge.html#merge-command"><span class="std std-ref">Merge</span></a> or <a class="reference internal" href="apps/split.html#split-command"><span class="std std-ref">split</span></a> data</li>
<li><a class="reference internal" href="apps/tindex.html#tindex-command"><span class="std std-ref">Catalog</span></a> collections of data</li>
</ul>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">The command line utilities are often simply <a class="reference internal" href="apps/pipeline.html#pipeline-command"><span class="std std-ref">pipeline</span></a> and
<a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">Pipeline</span></a> collected into a convenient application. In
many cases you can replicate the functionality of an application
entirely within a single pipeline.</p>
</div>
</div>
<div class="section" id="python-api">
<h3>Python API<a class="headerlink" href="#python-api" title="Permalink to this headline">¶</a></h3>
<p id="index-5">PDAL supports both embedding <a class="reference external" href="http://python.org/">Python</a> and extending with <a class="reference external" href="http://python.org/">Python</a>. These
allow you to dynamically interact with point cloud data in a more
comfortable and familiar language environment for geospatial practitioners.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last">The <a class="reference internal" href="python.html#python"><span class="std std-ref">Python</span></a> document contains information on how to
install and use the PDAL Python extension.</p>
</div>
</div>
</div>
<div class="section" id="conclusion">
<h2>Conclusion<a class="headerlink" href="#conclusion" title="Permalink to this headline">¶</a></h2>
<p>PDAL is an open source project for translating, filtering, and processing
point cloud data. It provides a C++ API, command line utilities, and Python
extensions. There are many open source software projects for interacting
with point cloud data, and PDAL’s niche is in processing, translation,
and automation.</p>
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