PDAL

PDAL, the Point Data Abstraction Library, is an open-source software library and application for working with 3D point cloud data. It provides a pipeline-based framework for ingesting, processing, analyzing, and exporting large LiDAR and other point cloud datasets. Written in C++ with bindings for Python and other languages, PDAL is designed to be modular and extensible through a system of readers, writers, filters, and spatial reference support. It is released under a permissive license (BSD-3-Clause).

Core concepts: A PDAL pipeline describes a sequence of stages that read data from a source, apply transformations, and write results to a destination. Stages come in three families: readers to import data, writers to export data, and filters to process data (for example, voxelization, statistical outlier removal, reprojection, or normalization). Pipelines can be configured in JSON or built programmatically, and can be executed via the pdal command-line tool or embedded in applications.

Supported formats and capabilities: PDAL can read and write multiple point cloud formats, notably LAS/LAZ, E57, PLY, and ASCII XYZ, and can translate between formats. It also supports coordinate reference system handling, metadata, and chunked processing for large datasets. Additional features include density estimation, ground and terrain classification, tiling, resampling, and statistical analysis.

Usage and ecosystem: PDAL is widely used in geospatial, surveying, and mapping workflows to preprocess and convert point cloud data, often as a preprocessing step before visualization or analysis in GIS and 3D modeling tools. It emphasizes reproducible workflows, scriptable pipelines, and integration with other software through its library and bindings.

Development and licensing: PDAL is an open-source project with an active community on GitHub. It is maintained by contributors and organizations in the geospatial community and licensed under BSD-3-Clause, promoting broad use and contribution.