For a long time I have been using softwares based in Windows to visualize and analyze LiDAR data sets for forest application. Recently, I have started to move all my work to Ubuntu platform, but I'm still looking for good softwares to work with LiDAR data sets.

Related to Windows the best free software experienced by me were:

  1. Just for visualization:

    a) Quick Terrain Reader is capable of opening pre-built digital elevation models (DEMs) and point clouds and allows users to freely move through the terrain in a fast and intuitive way.

    b) FugroViewer is a robust, easy-to-use freeware designed to help users make the most of their geospatial data.

    c) PointVue LE is a FREE 3-D LIDAR visualization tool which can be used to visualize LIDAR data in ASPRS LAS Version 1.1 format.

  2. For analyze and visualize:

    a) FUSION/LDV provides a fast, efficient and flexible access to LiDAR and terrain data sets.

Since I moved to Ubuntu, it was quite difficult to substitute the software I was used to use. Up to now, I found some alternatives but not so good as the Windows ones:

  1. For visualization:

    a) LiDAR visualization was implemented as an out-of-core multi resolution point cloud renderer. The renderer is able to visualize the largest LiDAR scans we currently have, containing up to 11.3 billion (11.3 * 109) sample points, at interactive frame rates using a fixed-size memory cache.

    b) LAG is a tool for visualisation, inspection and classification of LiDAR point clouds. It currently supports LAS and ASCII file formats.

Unfortunately, I couldn't find anything for processing like FUSION.

Has somebody experienced good free software to Linux related to LiDAR files analysis?

Do not just list other software, but explain why you use and recommend it!

  • Are you interested in database approaches too? It seems like storing it in PostGIS would be logical and open up a few other ways to viewing it (but I don't know your work-flow)
    – djq
    Jun 8, 2013 at 17:21
  • Did you get round to investigating any of these options. I made the move from Windows to Ubuntu a few years ago (no looking back) and am a major Postgres / PostGis fanboy, so I have been using Postgres for storage/analytics and python or webgl for viz, depending on context. Interested in your findings. Sep 16, 2017 at 13:23

7 Answers 7


SPDlib provides a very comprehensive line tools for processing Laser Scanning data (both Terrestrial and Airborne data). It is available for Linux and can be easily installed using Anaconda. SPDlib also has a viewer called that can be used to visualise point clouds (see screenshot). There is a number of very useful tutorials on available on the wiki and on this blog

enter image description here

Another recommendation is the Point Data Abstraction Library (PDAL), which provides extensive functionality for LiDAR processing and share similarities to GDAL.

  • In Anaconda the viewer itself is only available for MAC (source)
    – Kamiccolo
    Oct 19, 2017 at 13:57

Disclaimer: I'm on the development team.

We at the Vienna University of Technology have been developing a command-line tool for orientation and processing of airborne laser scan data for some time now. Since last summer, our product is available for Linux as well: OPALS. There is a free demo version supporting processing for up to a million points, as well as free licenses for academic thesis.

In my opinion, OPALS provides an excellent framework to experiment with point cloud data as well as program workflows to run automatically (scripting is possible via python and bash). A plugin for QGIS to provide a GUI is on it's way to release this summer (but only for windows, to start with).

The included point cloud viewer (opalsView) is based on MatLAB and might have trouble running on Linux, but I've seen that you have alternatives for that.

So my experience might be biased, but I wouldn't want to miss OPALS.


In general as you already mentioned the best software is only available for windows systems and you might get along with using WINE for your problem. Besides that:

  • GRASS is obvious your first and best choice and what i have been using most of the time. They even have a wiki-page explaining how to load/convert/analyse/visualize LiDAR data.
  • You can use the nice LAStools and GRASS/SAGA for processing and visualization.
  • Opticks also has LiDAR capabilities if i remember right
  • The BCal LiDAR tools also allow you to visualize LiDAR data (to be used with Envi software. Maybe you can consider using WINE)
  • 1
    as you noticed in my question I'm asking to share good softwares experiences. If you just google it you will find a lot of alternatives but not exactly the good ones. Here we can share more than links, but knowledge and opinions!
    – Gorgens
    Jun 8, 2013 at 15:14
  • 1
    indeed LASTools is a very good solution, but it is not free!
    – Gorgens
    Jun 8, 2013 at 15:15

Not directly to visualize the point cloud, but for processing it with some R packages. Examples: lidR and rLiDAR.

  • Please, don't just list software. Why do you use and recommend R and its respective packages? How do they compare to Fusion? Easy to use in Linux? How? May 31, 2018 at 21:20

There is a PostgreSQL Pointcloud extension for storing point cloud (LIDAR) data. Boundless has an excellent tutorial highlighting some of the functionality available with the extension. Essentially, this is a critical link in many LiDAR processing pipelines.

Building on dmci's answer, for forestry applications, SPDlib has a spdmetrics command that allows you to create grid metrics, a very popular FUSION feature.

  • 2
    That boundless tutorial is very helpful. I have been working on building geights and tree data recently from Lidar and other sources, and just found this answer. Thanks. Sep 16, 2017 at 13:01

For visualisation part, QGIS 3.18 and later can open PDAL data sources as stated in the release notes https://www.qgis.org/en/site/forusers/visualchangelog318/index.html#point-clouds

Visualisation can be done 2D and 3D. There surely ways for improvements but already a good step in particular when comparing various datasources.


Your best bet is ccViewer that comes with CloudCompare. It supports both Linux and MacOS. For analysis, I would look to tools in Python, R, or Julia. You can also compile LAStools for Linux as well it seems.

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