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  4. Evaluating the susceptibility of landslide landforms in Japan using slope stability analysis: a case study of the 2016 Kumamoto earthquake
 
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Evaluating the susceptibility of landslide landforms in Japan using slope stability analysis: a case study of the 2016 Kumamoto earthquake

Journal
Landslides
Journal Volume
14
Journal Issue
5
Pages
1793-1801
Date Issued
2017
Author(s)
CHI-WEN CHEN  
HONGEY CHEN  
Wei, L.-W.
Lin, G.-W.
Iida, T.
Ryuji Yamada
DOI
10.1007/s10346-017-0872-1
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/493107
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027295490&doi=10.1007%2fs10346-017-0872-1&partnerID=40&md5=d229f084b990d328f60ff3cf3e53325c
Abstract
This study analyzed 267 landslide landforms (LLs) in the Kumamoto area of Japan from the database of about 0.4 million LLs for the whole of Japan identified from aerial photos by the National Research Institute for Earth Science and Disaster Resilience of Japan (NIED). Each LL in the inventory is composed of a scarp and a moving mass. Since landslides are prone to reactivation, it is important to evaluate the sliding-recurrence susceptibility of LLs. One possible approach to evaluate the susceptibility of LLs is slope stability analysis. A previous study found a good correlation (R2 = 0.99) between the safety factor (Fs) and slope angle (α) of Fs = 17.3α−0.843. We applied the equation to the analysis of Fs for 267 LLs in the area affected by the 2016 Kumamoto earthquake (Mj = 7.3). The Fs was calculated for the following three cases of failure: scarps only, moving mass only, and scarps and moving mass together. Verification with the 2016 Kumamoto earthquake event shows that the most appropriate method for the evaluation of LLs is to consider the failure of scarps and moving mass together. In addition, by analyzing the relationship between the factors of slope of entire landslide and slope of scarp for LLs and comparing the results with the Aso-ohashi landslide, the largest landslide caused by the 2016 Kumamoto earthquake, we also found that morphometric analysis of LLs is useful for forecasting the travel distance of future landslides.
SDGs

[SDGs]SDG13

Type
journal article

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