Volume III-5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-5, 105-112, 2016
https://doi.org/10.5194/isprs-annals-III-5-105-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-5, 105-112, 2016
https://doi.org/10.5194/isprs-annals-III-5-105-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 Jun 2016

06 Jun 2016

3D GEOLOGICAL OUTCROP CHARACTERIZATION: AUTOMATIC DETECTION OF 3D PLANES (AZIMUTH AND DIP) USING LiDAR POINT CLOUDS

K. Anders1, M. Hämmerle1, G. Miernik2, T. Drews2, A. Escalona3, C. Townsend3, and B. Höfle1 K. Anders et al.
  • 1Institute of Geography, GIScience, LiDAR Research Group (LRG), Heidelberg University, Heidelberg, Germany
  • 2Institute of Earth Sciences, Heidelberg University, Heidelberg, Germany
  • 3Department of Petroleum Engineering, University of Stavanger, Stavanger, Norway

Keywords: LiDAR, Terrestrial laser scanning, 3D segmentation, Plane detection, Geological outcrop, Orientation, Strike

Abstract. Terrestrial laser scanning constitutes a powerful method in spatial information data acquisition and allows for geological outcrops to be captured with high resolution and accuracy. A crucial aspect for numerous geologic applications is the extraction of rock surface orientations from the data. This paper focuses on the detection of planes in rock surface data by applying a segmentation algorithm directly to a 3D point cloud. Its performance is assessed considering (1) reduced spatial resolution of data and (2) smoothing in the course of data pre-processing. The methodology is tested on simulations of progressively reduced spatial resolution defined by varying point cloud density. Smoothing of the point cloud data is implemented by modifying the neighborhood criteria during normals estima-tion. The considerable alteration of resulting planes emphasizes the influence of smoothing on the plane detection prior to the actual segmentation. Therefore, the parameter needs to be set in accordance with individual purposes and respective scales of studies. Fur-thermore, it is concluded that the quality of segmentation results does not decline even when the data volume is significantly reduced down to 10%. The azimuth and dip values of individual segments are determined for planes fit to the points belonging to one segment. Based on these results, azimuth and dip as well as strike character of the surface planes in the outcrop are assessed. Thereby, this paper contributes to a fully automatic and straightforward workflow for a comprehensive geometric description of outcrops in 3D.