How to Understand Point Cloud Classification in Airborne Lidar Measurement Technology?

Jun 02, 2023

"Point cloud" is actually transformed from a large number of dense three-dimensional discrete point data in airborne lidar measurement technology. Of course, "point cloud" data contains a variety of effective information, such as vegetation with reflection characteristics, ground and houses etc.

Building Classification and Extraction from Laser Point Cloud Data

The later "point cloud" data classification should be properly combined with the ground, vegetation or houses at different heights, and the wrong "flying points" should be eliminated as much as possible. Reflective ground objects will be reflected and accepted when they encounter laser light, so as to obtain recordable three-dimensional attribute reflection points. Therefore, the comparison between the specific elevation of the laser point and the elevation of the surrounding laser points should be based on the principle of "point cloud" data classification. Categorize automatically. Of course, this process also requires manual intervention and the rich experience of technicians to separate and process its "point cloud" data into its low ground vegetation.

Laser point cloud data vegetation classification and extraction P3C software

P3C, an airborne LiDAR data processing software independently developed by Feiyan Remote Sensing, is an airborne LiDAR data processing software independently developed with object-oriented thinking. Its functions include point cloud reading and writing, display, filtering, segmentation, classification, vector calculation, etc. , allows users to customize the data batch process, and the accuracy of extracting building points can reach more than 95%. The software has been used in hundreds of thousands of square kilometers of point cloud data processing, obtained three national invention patents and a software copyright authorization, and published a core journal paper.