Data compression system for LiDAR based on quad-tree structure

In recent years, three-dimensional (3D) data has become increasingly available, in part as a result of significant technological progresses in Light Detection and Ranging (LiDAR). LiDAR provides longitude and latitude information delivered in conjunction with a GPS device and elevation information generated by a pulse or phase laser scanner. The main advantages of LiDAR over conventional surveying methods lie in the high accuracy of the data and relatively little time needed to scan large geographical areas. On the basis of analyzing LiDAR data, we propose a compression system to simplify the data set which uses the quad-tree structure as a preprocessing step. The related theory and the methods to make it reality are discussed in detail. Some conclusions come from tests: the method presented in this paper can get a series of compression ratios, and can guarantee the accuracy of LiDAR data.