Assessing slope stability by ground based and remote techniques - a case study of 2015 Tbilisi disaster
Abstract
At the night of 13th of June 2015 complex-type landslide was triggered by heavy rainfall in the river Vere basin, 10 km to the west of Georgian capital Tbilisi. Flashflood flow transported the landslide body to the center of Tbilisi. As a result 20 people are dead and 2 still missing, direct infrastructure damage is about 50 mln USD. The landslide is located at Mtatsminda anticline, its length is 3600 meters and sliding surface area estimates 315 000 km2. Bedrock dips varies 20-800 and surface inclination is almost the same. Our group used geodetic, geophysical and UAV survey approaches to estimate total volume of landslide body. As a result of the investigation we calculated that 1 300 000 m3 was transported but about 25% of total amount is still on sliding surface. As the whole area is prone to landslide, different approaches were applied to assess slope stability and indentifing ongoing deformation areas. Two most challenging factors were steep terrain and forest cover, so we used InSAR techniques, optical remote sensing, RTK measurements and geophysical methods. The detection and assessment pre and post-failure deformation, represent important task to understand the failure mechanism and geometry of the landslide, an ultimately purpose is to evaluate its stability. Interferometric Synthetic Aperture Radar data from ENVISAT sensor was utilized in the analysis of the pre-/ post-event deformation. Also, Network of GNSS (Continuously Operating Reference Stations) was used for RTK, to provide centimeter precise measurements. After comparing results derived from these different approaches, proper methods were selected to identify the most unstable areas within the landslide zone.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMNH41B1775A
- Keywords:
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- 4326 Exposure;
- NATURAL HAZARDSDE: 4328 Risk;
- NATURAL HAZARDSDE: 4330 Vulnerability;
- NATURAL HAZARDSDE: 4337 Remote sensing and disasters;
- NATURAL HAZARDS