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AGILE: GIScience Series Open-access proceedings of the Association of Geographic Information Laboratories in Europe
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Articles | Volume 3
AGILE GIScience Ser., 3, 58, 2022
AGILE GIScience Ser., 3, 58, 2022
11 Jun 2022
11 Jun 2022

The use of high-resolution photogrammetry for the survey and analysis of rock-climbing walls

Stefan Ruess, Gernot Paulus, and Karl-Heinrich Anders Stefan Ruess et al.
  • Spatial Information Management, Faculty of Engineering and IT, Carinthia University of Applied Sciences, Villach, Austria

Keywords: 3D Point Cloud Analysis, Photogrammetry, 3D-Modelling, UAV

Abstract. In climbing, the routes that lead through a wall are mainly represented in two-dimensional maps. These climbing maps, also called "topos," help climbers and alpinists to plan their routes and find a way through the complex structures of a vertical or partially overhanging rock face. Today, a trend towards more realistic visualization techniques can be seen, where 3D representations are used for different geometric and topographic features (Kolecka, 2012). In this paper the focus is on 3D visualization and high-resolution data capturing at rock walls. Unmanned Aerial System (UAS) - based data collection has been conducted to collect digital images that are used to generate various outputs using a photogrammetry workflow. The photogrammetric processing of digital imagery results in dense 3D point clouds, digital surface models (DSM), textured 3D models and orthophotos of the test sites. How accurately is it possible to survey a vertical rock and how high the spatial resolution of the outputs will end up being is answered in this paper. After the data collection and the photogrammetric processing, a 3D climbing guide is created to answer the question if an enhanced visualization of climbing routes can be achieved. There are certain morphological features within the rock face that play a major role in climbing. For one, the climbing holds are important for climbers to continue the movement upwards. Other important factors are the dip angle and the dip direction of different rock facets. In this thesis the 3D point cloud is clustered into different sized facets, that share the same dip angle which is the angle of the center point of a cluster to a horizontal plane and the same dip direction which is the orientation of such a facet(Thanh, 2008). Using the analysis results, an automated climbing route construction is performed.

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