Build a PDAL JSON pipeline to read, reproject, filter, and write point cloud data
domain: pdal.io · 6 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗
Steps
Define a pipeline as a JSON array (or {"pipeline": [...]}) of PDAL Stage objects
Add a Reader stage matching your source format (e.g., a LAS/LAZ reader) as the first stage
Insert Filter stages as needed (e.g., reprojection to a target CRS, ground classification, outlier removal)
Add a Writer stage (e.g., a LAS writer or a database writer such as PostgreSQL/pgpointcloud) as the final stage
Run the pipeline with `pdal pipeline <file>.json`, or `pdal translate` for simple read/write-only cases
Rely on PDAL's stream mode (used automatically by translate/pipeline when supported) to keep memory usage low on large point clouds
Known gotchas
Not all stages support streaming; a pipeline mixing streaming-incompatible filters silently falls back to full in-memory processing
Stage order matters — e.g., reprojecting before a spatial filter behaves differently than reprojecting after
PDAL is a processing library/CLI, not a hosted API — reality-capture workflows usually pair it with a separate storage/viewer layer (e.g., Potree, Cesium ion)
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