Day 4

Detailed paper information

Back to list

Paper title Investigating the potential of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetric point cloud data for digital terrain model (DTM) extraction in a mixed grassland-dwarf shrubland environment
  1. Kuhle Ndyamboti Friedrich - Schiller - Universität - Jena Speaker
  2. Justin du Toit Grootfontein Agricultural Development Institute
  3. Kai Heckel Friedrich Schiller University Jena
  4. Jussi Baade Friedrich Schiller University Jena
  5. Christiane Schmullius University of Jena
  6. Christian Thau Team Geoinformation, City of Jena
Form of presentation Poster
  • C4. HAPs/UAVs
    • C4.01 Innovative UAV applications
Abstract text Digital terrain models (DTMs) are important for many environmental applications including hydrology, archaeology, geology, and the modelling of vegetation biophysical parameters such as above ground biomass (AGB) and vegetation height. The quality of a DTM depends on a number of factors including the method of data collection, with topographic surveys being considered as the most accurate DTM generation method. However, the logistical costs associated with conducting large-scale topographic surveys has seen a gradual decrease in their use for generating DTMs and newer technologies based on remote sensing have emerged. This study investigated the potential of utilizing terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetric point cloud data for generating DTMs in an area comprising a mixture of grass and dwarf shrubland vegetation near Middelburg, Eastern Cape, South Africa. An area covering approximately 13 200 m2 was surveyed using the Riegl VZ-1000 TLS instrument and the DJI Phantom 4 Pro drone. The TLS and UAV datasets were then co-registered into a common coordinate system using Real Time Kinematic Global Navigation Satellite System (RTK‐GNSS) reference measurements to yield overlapping point clouds in RiScan Pro 2.8 and AgiSoft Metashape version 1.6.1 softwares respectively. LASTools® point cloud processing software was subsequently used to compute DTMs from the georeferenced TLS and UAV datasets and independently collected checkpoints obtained from 8 TLS scan positions were used to validate the accuracy of the TLS and UAV-derived DTMs. The results from the study showed that DTMs generated from UAV photogrammetric point cloud data were comparable in accuracy to those generated from 3D TLS data, despite TLS-derived DTMs being slightly more accurate. This finding suggests that UAV photogrammetric point cloud data could be used as a cost-effective alternative to produce reliable estimates of surface topography in areas with short vegetation (maximum height less or equal to 2 m) and less complex terrain.