PDAL on the VDI - course under construction


This is a modular workshop demonstrating the Point Data Abstraction Library (PDAL) on NCI's VDI. We use PDAL release 1.3.0, documentation can be found here: http://www.pdal.io. it is aimed at NCI users who have had some exposure to working with point data obtained from airborne LiDAR, terrestrial LiDAR, 3D photogrammetry or multibeam bathymetry. Other point data formats exist, but are not yet useable in the PDAL ecosystem. Workshops on, for example, geophysical line data will be linked below as they arrive.

PDAL's own workshop documentation is extensive - please feel free to race through the materials at: http://www.pdal.io/workshop/index.html, which cover many of the topics presented in this workshop. If you get stuck, check the materials here - since they are tested on the VDI. If a really important example is missing please let us know!

What is PDAL

PDAL is a set of C libraries and command-line applications designed to work with topology-free point data (ie not gridded)

Why would I want to use PDAL?

PDAL was designed to meet the needs of users working with airborne LiDAR datasets. It has since grown to accomodate a number of different styles of point cloud data, and ways to use them. It was an early adopter of the LAS 1.4 community standard, and offers the best open-source, interoperable point cloud data processing engine we have seen to date.

Who is this course aimed at?

Users with some experience in point cloud analysis, geospatial techniques and at least some exposure to the Linux command line environment


Attendee skills

Data and resources


PDAL is a BSD-licensed open source product. Please review the license terms before deploying in your software stack.

Data used in this workshop come from the Geoscience Australia reference elevation collection, published via NCI's thredds catalogue and distributed under a CCBY4.0 license.

Workshop tasks

  1. Setup and test
  2. Basic translation
  3. PDAL pipelines
  4. Collecting a subset of a LiDAR survey
  5. Point selection by attribute - extracting a single class or intensity thresholding
  6. Some data QA tasks
  7. DSMs, DTMs, and Height-above-ground
  8. Visualising results
  9. PDAL + Python
  10. Interacting with Postgres-pointcloud

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