E3S Web of Conferences (Jan 2023)

Photogrammetrically UAV based terrain data generation and automatic extraction of torrential properties

  • Schmucki Gregor Rafael,
  • Bartelt Perry,
  • Bühler Yves,
  • Caviezel Andrin,
  • Graf Christoph,
  • Marty Mauro,
  • Stoffel Andreas,
  • Huggel Christian

DOI
https://doi.org/10.1051/e3sconf/202341503026
Journal volume & issue
Vol. 415
p. 03026

Abstract

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Debris flows are a severe hazard in mountainous regions. However, cost-effective long-term studies of debris flows are seldom, which leads to substantial uncertainties in hazard mitigation methods. This paper investigates whether cost-effective remote sensing techniques can be applied to assess the hazards of mountain torrents and to gather accurate long-term information on the development of the watershed. Torrents that are prone to debris flows are often devoid of vegetation and can thus be well surveyed using photogrammetric methods based on uncrewed aerial vehicle (UAV) surveys. The possibility of extracting automatically torrent parameters from high-resolution terrain models, such as cross-sectional area or slope, is explored. The presented methodology yields continuous and automatically derived parameters along the torrent, which is a major advantage over pointwise field surveys. Cross-validation with field measurements reveals a strong agreement. These parameters are very accurate along highly incised sections, while they are severely limited along sections with steep adjacent hillslopes and/or dense vegetation. We show that these kinds of assessments greatly gain from UAV data followed by automatic parameter extraction. The extracted parameters provide insights so that key sections and weak points can be identified and accurately assessed in the field. We find that UAV data can contribute to a comprehensive, reproducible and objective assessment of torrent processes and predispositions. However, ground-based fieldwork is still essential and further research on remote sensing-based hazard assessment of torrents prone to debris flows is crucial.