Laserfarm

Laserfarm (Laserchicken Framework for Applications in Research in Macro-ecology) provides a FOSS wrapper to Laserchicken supporting the use of massive LiDAR point cloud data sets for macro-ecology, from data preparation to scheduling and execution of distributed processing across a cluster of compute nodes.

Installation

The package can be downloaded using git:

git clone git@github.com:eEcoLiDAR/Laserfarm.git

It requires the PDAL and GDAL libraries and the PDAL Python bindings. These packages are most easily installed through conda from the conda-forge channel. The remaining dependencies can be retrieved and installed using pip:

conda install pdal python-pdal gdal -c conda-forge
cd Laserfarm && pip install . 

Alternatively, a new environment with the package and all its dependencies can be created from the YAML file provided:

conda env create -f environment.yml

Documentation

The project's full documentation can be found here.

Applications and Current Limitations

This package has been tested on data provided in a metric-based 2D-projected Cartesian coordinate system, i.e. the Actueel Hoogtebestand Nederland. While some of the tools of Laserfarm could be applied to data in an ellipsoidal latitude/longitude coordinate system as well, this has not been tested and it is generally expected to fail.

Contributing

If you want to contribute to the development of Laserfarm, have a look at the contribution guidelines.

License

Copyright (c) 2020, Netherlands eScience Center

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.