Brief communication: An autonomous UAV for catchment-wide monitoring of a debris flow torrent

Abstract

Abstract. Debris flows threaten communities in mountain regions worldwide. Combining modern photogrammetric processing with autonomous unoccupied aerial vehicle (UAV) flights at sub-weekly intervals allows mapping of sediment dynamics in a debris flow catchment. This provides important information for sediment disposition that pre-conditions the catchment for debris flow occurrence. At the Illgraben debris flow catchment in Switzerland, our autonomous UAV launched nearly 50 times in the snow-free periods in 2019–2021 with typical flight intervals of 2–4 d, producing 350–400 images every flight. The observed terrain changes resulting from debris flows exhibit preferred locations of erosion and deposition, including memory effects as previously deposited material is preferentially removed during subsequent debris flows. Such data are critical for the validation of geomorphological process models. Given the remote terrain, the mapped short-term erosion and deposition structures are difficult to obtain with conventional measurements. The proposed method thus fills an observational gap, which ground-based monitoring and satellite-based remote sensing cannot fill as a result of limited access, reaction time, spatial resolution, or involved costs.

Towards an automated acquisition and parametrization of debris‐flow prone torrent channel properties based on photogrammetric‐derived uncrewed aerial vehicle data

“…In the framework of this study, we have worked with different equipment and data sources with varying spatial resolutions and two different approaches for deriving surface data. UAV‐based terrain data have a main advantage to be acquired on a large scale with a high temporal resolution (Walter et al., 2022) at relatively low costs and limited risks (Giordan et al., 2018). We present the potential and the limitations of UAV‐based torrent analysis, focusing on the parameters that were investigated and measured in the presented study and indicate the potential relevance for hazard assessment.…”

“…For geomorphological assessments, an automatic morphological characterization of the torrent geometry allows for a more objective torrent analysis (Walter et al., 2022). We delineated the torrent bed, further segmented the adjacent embankments within the object‐based image analysis (OBIA) software eCognition, and finally extracted the torrential properties by transects.…”

“…In this work, we investigate how photogrammetric drone flights can be used to improve accuracy and efficiency in torrent mapping, specifically to obtain continuous estimates of torrent parameters and hence potential debris-flow volumes. Repeated photogrammetric uncrewed aerial vehicle (UAV) flights allow characterizing the development of landforms over time (Adams et al, 2016;Cucchiaro et al, 2018;de Haas et al, 2018;de Haas et al, 2020;Niculiț a et al, 2020;Passalacqua et al2015;Walter et al, 2022). Based on available spatial data, numerical simulation models of debris flows can be further developed and their parameters determined with greater accuracy (Graf et al, 2019).…”

“…ment and data sources with varying spatial resolutions and two different approaches for deriving surface data. UAV-based terrain data have a main advantage to be acquired on a large scale with a high temporal resolution(Walter et al, 2022) at relatively low costs andF I G U R E 9 Along densely vegetated shrub forests photogrammetric-derived routines are strongly limited, and classified ground points (colour highlighting) tend to be clearly above the LiDAR-based ground points. The ground point density of the high-resolution LiDAR along the densely vegetated areas is clearly superior compared to the low-resolution survey.…”

Application of UAV remote sensing in natural disaster monitoring and early warning: an example of flood and mudslide and earthquake disasters

“…In places such as the Illgraben in Switzerland, researchers such as Walter, Fabian and others have successfully used drone data comparison and analysis to detect signs of terrain change and predict where mudslides are likely to occur so that precautions can be taken in advance. The application of this technology is expected to improve monitoring efficiency and reduce potential disaster losses in areas with a high incidence of mudslides [6]. Zhou, B et al developed a UAV system that can be used to effectively monitor natural disasters such as mudslides and landslides.…”