ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-2-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 79–86, 2022
https://doi.org/10.5194/isprs-annals-V-2-2022-79-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 79–86, 2022
https://doi.org/10.5194/isprs-annals-V-2-2022-79-2022
 
17 May 2022
17 May 2022

VIRTUAL LASER SCANNING OF DYNAMIC SCENES CREATED FROM REAL 4D TOPOGRAPHIC POINT CLOUD DATA

L. Winiwarter1, K. Anders1, D. Schröder2,3, and B. Höfle1,4 L. Winiwarter et al.
  • 13DGeo Research Group, Institute of Geography, Heidelberg University, Germany
  • 2Department of Civil and Mining Engineering, DMT GmbH & Co. KG, Essen, Germany
  • 3Faculty of Geoscience, Geotechnology and Mining, University of Mining and Technology Freiberg, Germany
  • 4Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany

Keywords: LiDAR simulation, scene generation, change object, virtual scenes, change detection

Abstract. Virtual laser scanning (VLS) allows the generation of realistic point cloud data at a fraction of the costs required for real acquisitions. It also allows carrying out experiments that would not be feasible or even impossible in the real world, e.g., due to time constraints or when hardware does not exist. A critical part of a simulation is an adequate substitution of reality. In the case of VLS, this concerns the scanner, the laser-object interaction, and the scene. In this contribution, we present a method to recreate a realistic dynamic scene, where the surface changes over time. We first apply change detection and quantification on a real dataset of an erosion-affected high-mountain slope in Tyrol, Austria, acquired with permanent terrestrial laser scanning (TLS). Then, we model and extract the time series of a single change form, and transfer it to a virtual model scene. The benefit of such a transfer is that no physical modelling of the change processes is required. In our example, we use a Kalman filter with subsequent clustering to extract a set of erosion rills from a time series of high-resolution TLS data. The change magnitudes quantified at the locations of these rills are then transferred to a triangular mesh, representing the virtual scene. Subsequently, we apply VLS to investigate the detectability of such erosion rills from airborne laser scanning at multiple subsequent points in time. This enables us to test if, e.g., a certain flying altitude is appropriate in a disaster response setting for the detection of areas exposed to immediate danger. To ensure a successful transfer, the spatial resolution and the accuracy of the input dataset are much higher than the accuracy and resolution that are being simulated. Furthermore, the investigated change form is detected as significant in the input data. We, therefore, conclude the model of the dynamic scene derived from real TLS data to be an appropriate substitution for reality.