Volume IV-2/W4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 259-266, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 259-266, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Sep 2017

13 Sep 2017

IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND DENSE IMAGE MATCHING

G. Mandlburger1,2, K. Wenzel3, A. Spitzer4, N. Haala2, P. Glira1,5, and N. Pfeifer1 G. Mandlburger et al.
  • 1TU Vienna, Department of Geodesy and Geoinformation, Vienna, Austria
  • 2University of Stuttgart, Institute for Photogrammetry, Stuttgart, Germany
  • 3nFrames GmbH, Stuttgart, Germany
  • 4RIEGL Laser Measurement Systems, Horn, Austria
  • 5Siemens AG, Corporate Technology (CT), Vienna, Austria

Keywords: Airborne laser scanning, aerial images, digital surface model, sensor orientation, data fusion

Abstract. Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the RIEGL LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i) systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii) systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii) improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.