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Issue No. 05 - September/October (2017 vol. 37)
ISSN: 0272-1716
pp: 72-84
Jules Morel , French Institute of Pondicherry and Aix-Marseille University
Alexandra Bac , Aix-Marseille University
Cedric Vega , National Institute of Geographic and Forest Information
ABSTRACT
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.
INDEX TERMS
Geographic information systems, Vegetation mapping, Geophysical measurement techniques, Terrain mapping, Digital systems, Radial basis function networks
CITATION

J. Morel, A. Bac and C. Vega, "Terrain Model Reconstruction from Terrestrial LiDAR Data Using Radial Basis Functions," in IEEE Computer Graphics and Applications, vol. 37, no. 5, pp. 72-84, 2017.
doi:10.1109/MCG.2017.3621225
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