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Point clouds in QGIS: Now with Processing integration!

Martin Dobiaš

Lutra Consulting

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QGIS user conference 2023

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About Lutra Consulting

  • Services around open source GIS
    • QGIS development
    • Development of custom QGIS plugins
    • Migration to open source GIS
    • Support and training�
  • Mergin Maps: Mobile data collection
    • Mobile app based on QGIS (Android/iOS)
    • Web service for synchronization
    • QGIS plugin for setup
    • Hosted SaaS, open source community edition
    • https://merginmaps.com/�

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Point clouds in QGIS

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Point clouds in QGIS

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Challenges of point cloud data

  • Massive amounts of points
  • Commonly used formats (LAS/LAZ)�not optimized for 2D/3D viewing

Data need to be organized (indexed)�before rendering.

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Eye-dome lighting in 3D

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Eye-dome lighting in 2D (3.28)

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Ordered rendering in 2D (3.24)

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Default

Bottom to top

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Better classified renderer (3.26)

  • Skip display of unused classes
  • Show non-standard classes
  • Percentage of points for each class

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Filtering of point clouds (3.26)

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Sync 2D and 3D style of point clouds (3.26)

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Point clouds as surfaces (3.26)

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Export of point clouds (3.28)

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Cloud-optimized Point Cloud (COPC)

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Cloud-optimized Point Cloud (COPC)

  • https://copc.io/
  • Similar idea to Cloud-optimized GeoTIFF applied to point clouds
  • Ordinary compressed LAZ file
  • File content reorganized for efficient access to data even if the file is on a remote server
  • Easy to use in client software, no need to further process (index) data�
  • Both local and remote COPC files supported since QGIS 3.26!

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Remote datasets (COPC or EPT)

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Remote datasets (COPC or EPT)

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Point cloud processing

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PDAL - Point Data Abstraction Library

  • “GDAL for point cloud data”
  • Drivers to read/write multitude of formats
  • Wide range of filters for manipulation of data
  • Combine readers, writers and filters into pipelines

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pdal_wrench: New command line tool

  • https://github.com/PDAL/wrench
  • Single executable with multiple commands, e.g.:
    • pdal_wrench boundary --input=data.las --output=boundary.gpkg
    • pdal_wrench to_raster -–input=data.las --output=raster.tif \� --resolution=1 --attribute=Z �
  • Ease of use - no need to build JSON pipelines for PDAL
  • Runs the processing in parallel
    • If the input is a COPC / EPT or there are multiple input files

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New algorithms added

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Clip by polygon

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Density

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Filter (by expression)

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Extract boundary

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Convert to raster

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More algorithms

  • Thinning
  • Export points as a vector layer
  • Merge data
  • Tile data
  • Convert format (e.g. LAS->LAZ)
  • Info
  • Reproject
  • Fix projection

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Virtual point clouds

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Virtual point clouds

  • A way how to deal with large datasets (billions of points)
  • Concept similar to GDAL’s virtual rasters (VRT)
  • A single JSON file that references actual files of the dataset (e.g. las/laz)
  • Format: STAC API ItemCollection … GeoJSON with some extra fields
  • Reference local files on file system or remote files

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Virtual point clouds in QGIS

  • A new data provider
  • 2D and 3D rendering support�is being implemented right now
  • Processing algorithms support�virtual point clouds!
    • Including algorithm to create�a virtual point cloud

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What’s next?

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What’s next?

  • More point cloud processing algorithms
    • Classification
    • Noise reduction
    • Height above ground
    • Convert to 3D mesh
    • Colorize point clouds
    • …�
  • “Digital twins” ? 3D mesh with texturing

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Thank you!

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martin.dobias@lutraconsulting.co.uk

Twitter: @lutraconsulting