A research on organization and rapid allocation method for large-scale 3D points cloud data

Now, 3D GIS, in the Z expansion of 2D GIS, receives more and more people´s attention. It can express the real world and the surface morphology better, will certainly to be an important direction of GIS development. But no matter what kind of 3D data sources, vast amounts of data has been a major bottleneck impeding their development. In this paper, for 3D laser point cloud data, which is one of 3D GIS data sources, I try to propose one kind of method octree-based to organize and allocate points cloud data rapidly, it also lays a solid foundation for the further analysis of 3D points data. Finally, application examples demonstrate the effectiveness and accuracy of this method.