# PDAL/PDAL

PDAL is Point Data Abstraction Library. GDAL for point cloud data.

Repository: https://github.com/PDAL/PDAL
Canonical: https://ross.abutalabs.com/products/pdal
Homepage: https://pdal.io
Language: C++
License: NOASSERTION
License Family: other
Last push: 2026-08-26T18:45:14+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 76, longevity 100
- inputs: {"age_days": 5493, "days_push": 7, "days_rel": 82, "gap_med": 49, "n_releases_24m": 12}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1404, forks 507 (observed 2026-08-28T04:04:38.079848+00:00)

## What it is
PDAL (Point Data Abstraction Library) is a C++ library and suite of command-line applications for translating, filtering, and manipulating point cloud data, analogous to GDAL for raster/vector data. It composes processing operations into declarative JSON pipelines of reader, filter, and writer stages, and offers Python bindings.

## Use cases
- convert LAS/LAZ LiDAR files to other formats
- reproject point cloud data to a different coordinate system
- load LiDAR data into a PostgreSQL database
- filter and classify point clouds with pipelines
- compute geometric feature descriptors on point neighborhoods
- inspect and query point cloud file metadata from the command line

## When to choose
- you need a mature, format-agnostic tool for reading, writing, and transforming point cloud data
- you want composable, reusable processing pipelines instead of monolithic one-off scripts
- you work with LiDAR or other point cloud formats like ASPRS LAS
- you need Python integration for point cloud processing workflows

## When to avoid
- you only work with raster or vector geospatial data, where GDAL is the better fit
- you need mesh processing or 3D surface modeling rather than point cloud handling
- you need a lightweight pure-Python solution without C++ dependencies

## Facets
- artifact type: library
- maturity: stable
- function: file-system, data-science, cli, sdk, plugin-system
- domain: files, developer-tools
- platform: windows, cpp, python, cross-platform, cli
- tags: point-cloud, lidar, las, gdal, pipeline, geospatial-data, point-cloud-processing, geospatial, data-engineering, linux, macos

## Member repositories
- PDAL/PDAL (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:38.079848+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:38:49.041165+00:00, confidence not recorded.
  - readme: https://github.com/PDAL/PDAL (fetched 2026-08-28T04:04:38.079848+00:00, sha 63b65e4bd19f)
  - homepage: https://pdal.io (fetched 2026-08-29T11:52:40.376751+00:00, sha 605fc675151b)
  - site_page: https://pdal.org/en/2.10.2/about.html (fetched 2026-08-29T11:52:40.385989+00:00, sha 3ba74a7023cd)
  - site_page: https://pdal.org/en/2.10.2/quickstart.html (fetched 2026-08-29T11:52:40.388700+00:00, sha 4d800b401b81)
  - site_page: https://pdal.org/en/2.10.2/stages/filters.covariancefeatures.html (fetched 2026-08-29T11:52:40.391649+00:00, sha 7721e613c8c8)
  - site_page: https://pdal.org/en/2.10.2/development/docs.html (fetched 2026-08-29T11:52:40.396720+00:00, sha e5fa04160531)
  - site_page: https://pdal.org/en/2.10.2/workshop/software.html (fetched 2026-08-29T11:52:40.394339+00:00, sha a982d810d177)
  - site_page: https://pdal.org/en/2.10.2/faq.html (fetched 2026-08-29T11:52:40.398731+00:00, sha 267fac771a72)
- Data as of 2026-08-30T08:39:29.467469+00:00.