Japan Geoscience Union Meeting 2018

Presentation information

[EE] Poster

M (Multidisciplinary and Interdisciplinary) » M-TT Technology & Techniques


Sun. May 20, 2018 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall7, Makuhari Messe)

convener:Yuichi S. Hayakawa(Center for Spatial Information Science, The University of Tokyo), Christopher A Gomez (Kobe University Faculty of Maritime Sciences Volcanic Risk at Sea Research Group), Shigekazu Kusumoto(富山大学大学院理工学研究部(理学))

[MTT35-P01] Spatial distribution of landslides in Sensuikyo Area in the Aso region induced by the 2016 Kumamoto Earthquake

*Yasutaka Haneda1, Takashi Oguchi2, Yuichi S. Hayakawa2, Hitoshi SAITO3, Shoichiro Uchiyama4 (1.Graduate School of Frontier Science, The University of Tokyo, 2.Center for Spatial Information Science, The University of Tokyo, 3.College of Economics, Kanto Gakuin University, 4.National Research Institute for Earth Science and Disaster Prevention)

Keywords:the 2016 Kumamoto earthquake, Unmanned Aerial Vehicle (drone), Terrestrial Laser Scanning (TLS), Landslides, High-Definition topography

The 2016 Kumamoto earthquake triggered many landslides on steep slopes in the Sensuikyo area near Aso Volcano in Kumamoto, western Japan. We conducted field surveys on terrain shape information by Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle in order to discuss the effect of the earthquake. We analyze dense point cloud data of TLS in terms of the elevation change and topographic profile shapes. The maximum depth of the earthquake-derived landslides is about 6 m, which is deeper than the past landslides induced by heavy rainfalls. We also found that the longitudinal profiles of earthquake triggered landslides show different shapes from those of rainfall triggered landslides: The former are more curved, whereas the latter are straighter. This suggest that the landslides driven by the earthquake have occurred along a slip surface deeper than that of the rainfall-derived landslides. In this presentation, we discuss the detailed spatial distribution of landslides using a UAV-derived digital surface model and it derivative such as slope.