Volume IV-2/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 567-574, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-567-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 567-574, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-567-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 May 2019

29 May 2019

HYBRID ORIENTATION OF AIRBORNE LIDAR POINT CLOUDS AND AERIAL IMAGES

P. Glira1,2, N. Pfeifer1, and G. Mandlburger1,3 P. Glira et al.
  • 1TU Vienna, Department of Geodesy and Geoinformation, Vienna, Austria
  • 2Austrian Institute of Technology (AIT), Vienna, Austria
  • 3University of Stuttgart, Institute for Photogrammetry, Stuttgart, Germany

Keywords: orientation, calibration, strip adjustment, aerial triangulation, hybrid adjustment

Abstract. Airborne LiDAR (Light Detection And Ranging) and airborne photogrammetry are both proven and widely used techniques for the 3D topographic mapping of extended areas. Although both techniques are based on different reconstruction principles (polar measurement vs. ray triangulation), they ultimately serve the same purpose, the 3D reconstruction of the Earth’s surface, natural objects or infrastructure. It is therefore obvious for many applications to integrate the data from both techniques to generate more accurate and complete results. Many works have been published on this topic of data fusion. However, no rigorous integrated solution exists for the first two steps that need to be carried out after data acquisition, namely (a) the lidar strip adjustment and (b) the aerial triangulation. A consequence of solving these two optimization problems independently can be large discrepancies (of up to several decimeters) between the lidar block and the image block. This is especially the case in challenging situations, e.g. corridor mapping with one strip only or in case few or no ground control data. To avoid this problem and thereby profit from many other advantages, a first rigorous integration of these two tasks, the hybrid orientation of lidar point clouds and aerial images, is presented in this work.