libClidar

A collection of C programs and libraries for processing lidar data, including voxelisation of terrestrial and airborne laser scanning (TLS/ALS) point clouds, simulation of large-footprint full-waveform lidar (e.g. GEDI), and estimation of plant area index (PAI) and 3D vegetation structure.

Developed by Steven Hancock. Released under the GNU General Public License v3.

Components

Directory	Description	Key tools
libclidar	Core C library for lidar I/O and voxel operations	(library only)
gedisimulator	Simulates large-footprint full-waveform lidar from ALS data	gediRat, gediMetric, mapLidar, lasPoints, collocateWaves, addNoiseHDF
voxelate	Creates voxel maps from full-waveform ALS or TLS data	voxelate, voxelTLS, dumpTLScloud, voxDecimate
voxel_lidar	PAI mapping and gap-fraction calibration from ALS+TLS	optimiseTLS, rxpVox
rxptobinary	Converts Riegl .rxp scan files to binary or ASCII	readRXP
salcamake	Processes data from the SALCA dual-wavelength TLS	hedgehog, salcaCal, tiffSALCA

Dependencies

• System libraries: GSL, HDF5, GDAL, libgeotiff, libtiff, proj
• Hancock C-tools: https://bitbucket.org/StevenHancock/tools
• cmpfit / Minpack: https://www.physics.wisc.edu/~craigm/idl/cmpfit.html
• Riegl RiVLib (for readRXP only): proprietary, not included

Building with Dev Container

A .devcontainer configuration is provided for building all components. It uses Fedora 43 and installs all required dependencies automatically.

Prerequisites

• Docker or Podman
• VS Code with the Dev Containers extension (or any devcontainer-compatible tool)
• Riegl RiVLib and RDBLib archives placed in riegl_libs/:
  • rivlib-2_6_0-x86_64-linux-gcc11.zip
  • rdblib-2.4.1-x86_64-linux.tar.gz

Usage

1. Open the project in VS Code and select Reopen in Container, or build manually:

   cd .devcontainer
   docker build -t libclidar -f Dockerfile ..
   docker run -it -v $(pwd)/..:/workspaces/libClidar libclidar bash

2. Inside the container, run the build script:

   bash .devcontainer/build-all.sh

   Compiled binaries are placed in bin/.

Environment variables

The container sets these automatically. If building outside the container, you must define them:

Variable	Description
HANCOCKTOOLS_ROOT	Path to Hancock C-tools
CMPFIT_ROOT	Path to cmpfit/Minpack
LIBCLIDAR_ROOT	Path to libclidar/
VOXELATE_ROOT	Path to voxelate/
GEDIRAT_ROOT	Path to gedisimulator/
GSL_ROOT	Path to GSL library
HDF5_LIB	Path to HDF5 installation
RiVLib_DIR	Path to RiVLib (for readRXP)

Standalone Docker image

A multi-stage Dockerfile builds all tools and produces a minimal runtime image (~2.2 GB) with every binary on PATH.

# Build (requires riegl_libs/ in the repo root)
docker build -t libclidar .

# Run interactively with data mounted
docker run --rm -it -v /path/to/scans:/data libclidar

# Run a single command
docker run --rm -v /path/to/scans:/data libclidar -c \
  "readRXP -input /data/scan.rxp -output /data/scan.bin -trans /data/scan.DAT"

Example: TLS voxelisation pipeline

# 1. Convert Riegl RXP to binary format (applying SOP transform)
readRXP -input scan.rxp -output scan.bin -trans scan.DAT

# 2. Create voxel map (1m resolution)
voxelTLS -input scan.bin -res 1 1 1 -output voxels.dat

# 3. Export voxel point cloud
dumpTLScloud -input voxels.dat -output cloud.asc

References

• Hancock, S., et al. (2019). The GEDI Simulator: A Large-Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions. Earth and Space Science, 6, 294-310.

License

GNU General Public License v3.0 -- see individual source file headers for details.