The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B5-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 173–178, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-173-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 173–178, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-173-2020

  24 Aug 2020

24 Aug 2020

MORPHOLOGICAL ANALYSIS OF LANDSLIDES IN EXTREME TOPOGRAPHY BY UAS-SfM: DATA ACQUISITION, 3D MODELS AND CHANGE DETECTION

T. W. Yeh and R. Y. Chuang T. W. Yeh and R. Y. Chuang
  • Department of Geography, National Taiwan University, Taipei, Taiwan

Keywords: Unmanned Aerial Vehicles, Multi-View Stereo, Point Clouds, Mass Wasting, Landslides, Extreme Topography

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.