Abstract
Abstract. Landslides are one major kind of natural disasters and geomorphological processes on Earth’s surface. Accurate geodetic observations are crucial for understanding morphological changes, providing a quantitative basis of further research in surface process and hazard management. In recent years, the development of UAVs and SfM technology enhance research to build high quality digital surface models of landforms with low budget and efficiency. In areas of extreme topography where landslides occur on steep slopes, however, it is required to specifically design the UAV-SfM workflow to keep the data quality. This study aims to use UAS-SfM workflow to develop a low-cost, efficient methodology to detect detailed morphological change of landslide morphology in extreme topography. The study focuses on examining results of different flight design and GCPs distribution geometry, which are important components in the workflow. In addition, we applied a mathematical model to compare point clouds to calculate volumetric change of the landslide with reduced distortion.
Highlights
The process of mass wasting is one fundamental question in earth sciences, which is highly related to research in geomorphology and hazard management
We examined different observation settings by using Unmanned Aerial Vehicle (UAV) and deploying ground control points (GCPs) for a landslide with extreme topography within an active mountain belt in south eastern Taiwan
Our results show that when applying the UAV-Structure from Motion (SfM) methods on steep targets, the flight line should be arranged vertically on different elevation so that the images can contain the full extent of façade, which help produce enough tie points in SfM processing
Summary
The process of mass wasting is one fundamental question in earth sciences, which is highly related to research in geomorphology and hazard management. In order to analyse the process, it is important monitor and detect surficial changes of landslides, and geodetic approaches are often used to conduct such observations. Compared with traditional geodetic techniques, UAV-SfM workflow allow researchers to quantify and analyse the morphological change of landslides in a laboursaving, safe and efficient way. The characteristics of SfM, which cannot straightforwardly infer uncertainty following traditional photogrammetric algorithm, inspire studies to further examine the source of errors from flight design, geometry of ground-reference points and photography settings in order to achieve high precision of 3D models. The purpose of this study aims to develop a suitable UAS-SfM workflow to landslides with extreme topography and examine how the procedures is applied to detect morphological changes. We tested different flight design and GCP geometry to examine their data quality for observing landslide volumes
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