Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 45-49, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
07 Nov 2014
Terrestrial Method for Airborne Lidar Quality Control and Assessment
N. M. Alsubaie1, H. M. Badawy1, M. M. Elhabiby2, and N. El-Sheimy1 1Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
2Public Works Department, Ain Shams University, Cairo, Egypt
Keywords: LiDAR, accuracy, quality control, error Assessment Abstract. Most of LiDAR systems do not provide the end user with the calibration and acquisition procedures that can use to validate the quality of the data acquired by the airborne system. Therefore, this system needs data Quality Control (QC) and assessment procedures to verify the accuracy of the laser footprints and mainly at building edges. This research paper introduces an efficient method for validating the quality of the airborne LiDAR point clouds data using terrestrial laser scanning data integrated with edge detection techniques. This method will be based on detecting the edge of buildings from these two independent systems. Hence, the building edges are extracted from the airborne data using an algorithm that is based on the standard deviation of neighbour point's height from certain threshold with respect to centre points using radius threshold. The algorithm is adaptive to different point densities. The approach is combined with another innovative edge detection technique from terrestrial laser scanning point clouds that is based on the height and point density constraints. Finally, statistical analysis and assessment will be applied to compare these two systems in term of edge detection extraction precision, which will be a priori step for 3D city modelling generated from heterogeneous LiDAR systems
Conference paper (PDF, 617 KB)

Citation: Alsubaie, N. M., Badawy, H. M., Elhabiby, M. M., and El-Sheimy, N.: Terrestrial Method for Airborne Lidar Quality Control and Assessment, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 45-49,, 2014.

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