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Remote Sens. 2014, 6(12), 12686-12707; doi:10.3390/rs61212686

Surface-Based Registration of Airborne and Terrestrial Mobile LiDAR Point Clouds

Department of Civil Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
Author to whom correspondence should be addressed.
Received: 9 October 2014 / Revised: 8 December 2014 / Accepted: 15 December 2014 / Published: 17 December 2014
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Light Detection and Ranging (LiDAR) is an active sensor that can effectively acquire a large number of three-dimensional (3-D) points. LiDAR systems can be equipped on different platforms for different applications, but to integrate the data, point cloud registration is needed to improve geometric consistency. The registration of airborne and terrestrial mobile LiDAR is a challenging task because the point densities and scanning directions differ. We proposed a scheme for the registration of airborne and terrestrial mobile LiDAR using the least squares 3-D surface registration technique to minimize the surfaces between two datasets. To analyze the effect of point density in registration, the simulation data simulated different conditions and estimated the theoretical errors. The test data were the point clouds of the airborne LiDAR system (ALS) and the mobile LiDAR system (MLS), which were acquired by Optech ALTM 3070 and Lynx, respectively. The resulting simulation analysis indicated that the accuracy of registration improved as the density increased. For the test dataset, the registration error of mobile LiDAR between different trajectories improved from 40 cm to 4 cm, and the registration error between ALS and MLS improved from 84 cm to 4 cm. These results indicate that the proposed methods can obtain 5 cm accuracy between ALS and MLS. View Full-Text
Keywords: LiDAR; point clouds; least squares surface matching; registration LiDAR; point clouds; least squares surface matching; registration

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Teo, T.-A.; Huang, S.-H. Surface-Based Registration of Airborne and Terrestrial Mobile LiDAR Point Clouds. Remote Sens. 2014, 6, 12686-12707.

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