Automatic Ground Classification of Dense Point Clouds in LP360
Published On: November 12, 2017
The density of LIDAR and drone mapping point clouds (usually expressed as points per square meter) is increasing on what seems to be a monthly basis. This is particularly true of point clouds derived from Dense Image Matching (DIM), the clouds produced from software such as PhotoScan, Pix4D, DroneDeploy and so forth. This article provides workflows to handle these large datasets for automatic ground classification using LP360 a software for LIDAR and 3D point clouds from DIM.