AUTOMATIC EXTRACTION OF CONTROL POINTS FROM 3D LIDAR MOBILE MAPPING AND UAV IMAGERY FOR AERIAL TRIANGULATION

Abstract. Installing targets and measuring them as ground control points (GCPs) are time consuming cost inefficient tasks in a UAV photogrammetry project. This research aims to automatically extract GCPs from 3D LiDAR mobile mapping system (L-MMS) measurements imagery perform aerial triangulation photogrammetric network. The L-MMS allows acquire point clouds of an urban environment including floors facades buildings with accuracy few centimetres. Integration imagery, complementary information enables reduce the acquisition measurement well increasing automation level production line. Therefore, higher quality more diverse products obtained. hypothesises that spatial is than clouds. tie extracted based on well-known SIFT method, then matched. structure motion (SfM) algorithm applied estimate object coordinates matched points. Rigid registration carried out between obtained SfM. For each SfM clouds, their corresponding neighbouring selected plane fitted was projected plane, this how LiDAR-based (LCPs) calculated. re-projection error analyses test data sets Glian area Iran show half pixel size standing for centimetres range accuracy. Finally, significant speed up survey operations besides improving LCPs achieved.