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EN
3D urban building models play an important role in the association, convergence and integration of economic and social urban data. 3D building reconstruction can be done from both the lidar and image-based point clouds, however, the lidar point clouds has dominated the research giving the 3D buildings reconstruction from aerial images point clouds less attention. The UAV images can be acquired at low cost, the workflow can be automated with minimal technical knowhow limitation. This promotes the necessity to understand and question to what extent the 3D buildings from UAV point clouds are complete and correct from data processing to parameter settings. This study focuses on proposing a process for building 3D geospatial data for a smart city using geospatial data collected by UAV and Terrestrial Laser Scanner. The experimental results have produced 3D geospatial data of high building in LoD3, with the root mean square error of the received test points mΔx=3.8 cm, mΔy=3.1 cm, and mΔH=7.5 cm.
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