Japan Geoscience Union Meeting 2022

Presentation information

[E] Poster

H (Human Geosciences ) » H-DS Disaster geosciences

[H-DS07] Landslides and related phenomena

Wed. Jun 1, 2022 4:00 PM - 6:00 PM Online Poster Zoom Room (16) (Ch.16)

convener:Masahiro Chigira(Fukada Geological Institute), convener:Gonghui Wang(Disaster Prevention Research Institute, Kyoto University), Fumitoshi Imaizumi(Faculty of Agriculture, Shizuoka University), Chairperson:Ching-Ying Tsou(Faculty of Agriculture and Life Science, Hirosaki University), Makoto Msatsuzawa(Fukada Geological Institute)

4:00 PM - 6:00 PM

[HDS07-P07] Mapping and interpretation of potential deep-seated landslides in Taiwan using high resolution LiDAR-derived DEM

★Invited Papers

*Ying-Hung Tung1, Yu-Chung Hsieh1, Hsi-Hung Lin1, Chung-Chi Chi1 (1.Central Geological Survey, Ministry of Economic Affairs, R.O.C. (Taiwan))

After surveying of high-resolution digital elevation model (DEM) of the entire Taiwan Island using air-borne LiDAR in 2015, Central Geological Survey (CGS) in Taiwan has continued to map and interpret potential deep-seated landslides with geomorphological features revealed by 1-m DEM. Until 2021, a project focusing on hill and mountain area near settlements had been conducted, and 2,500 potential landslides with area greater than 10 ha near settlements and 2,558 potential landslides with area less than 10 ha have been identified. In this stage, three aspects could be addressed. First, the result could provide us an overall discovery of geologically sensitive factors, such as gully erosion, dip slopes, and potential landslides, which may influence adjacent settlements. Second, with the landslide scarps, erosional gullies, and nearby lineations identified, the relationships between geomorphological evolution and geological setting could be deduced. Third, this inventory of potential landslides could be utilized for disaster prevention and reduction, and for planning of land use. And among potential landslides identified, some of them were reactivated during intense precipitation events in recent years. However, as potential landslides away from settlements may also impact much on transportation system, natural environment, as well as human activities, survey covering much area is continuing to map potential deep-seated landslides in Taiwan especially in mountainous area. Otherwise, because a single-period LiDAR DEM provides geomorphological information only in one period, the changes of surface are not observed, the adoption of multi-temporal LiDAR DEM and other in situ or remote sensing methodology is necessary to assess the activity, susceptibility, and hazard of potential landslides more comprehensively.