Ground Profile Recovery from Aerial 3D LiDAR-based Maps
This work addresses terrain mapping for forestry applications, but it is incremental as it applies an existing method to new data.
The paper tackled ground detection and forest point removal from aerial 3D LiDAR point clouds using the Cloth Simulation Filtering algorithm, recovering terrestrial relief and creating landscape maps for a forestry region, with an outdoor flight experiment demonstrating encouraging results for ground detection and robustness.
The paper presents the study and implementation of the ground detection methodology with filtration and removal of forest points from LiDAR-based 3D point cloud using the Cloth Simulation Filtering (CSF) algorithm. The methodology allows to recover a terrestrial relief and create a landscape map of a forestry region. As the proof-of-concept, we provided the outdoor flight experiment, launching a hexacopter under a mixed forestry region with sharp ground changes nearby Innopolis city (Russia), which demonstrated the encouraging results for both ground detection and methodology robustness.