Toolkit for preprocessing and feature calculation of point clouds created using airborne laser scanning
Laserchicken is a user-extendable, cross-platform Python tool for extracting statistical properties (features in machine learning jargon) of flexibly defined subsets of point cloud data.
Laserchicken loads a point-cloud from a LAS or LAZ or PLY file. After this, it can filter points by various criteria, and it can normalize the height. Laserchicken can load another point cloud, which contains targets. For every target point, Laserchicken computes its neighbors. Based on the list of neighbors, Laserchicken extracts features that effectively describe the neighborhood of each target point.
eScience infrastructure for ecological applications of LiDAR point clouds