Terrain Model Reconstruction from Terrestrial LiDAR Data Using Radial Basis Functions

IEEE Comput Graph Appl. 2017;37(5):72-84. doi: 10.1109/MCG.2017.3621225.


The presence of vegetation and the terrain topography itself generate strong occlusions causing large gaps in terrestrial laser scanning (TLS) data at the ground level as well as a risk of integrating above-ground objects. This article introduces a surface-approximation algorithm dedicated to extracting digital terrain models (DTMs) from terrestrial TLS data acquired in forest areas. The proposed method is based on the combination of a quadtree subdivision of space guided by the local density and distribution of data together with a surface modeling via radial basis functions, which are used as partitions of unity for merging local quadratic approximating patches.

Publication types

  • Research Support, Non-U.S. Gov't