Application of a GIS-based slope unit method for landslide susceptibility mapping along the rapidly uplifting section of the upper Jinsha River, South-Western China-Reference-Cited by-同舟云学术

Application of a GIS-based slope unit method for landslide susceptibility mapping along the rapidly uplifting section of the upper Jinsha River, South-Western China

Published:2019-07-05 Issue:1 Volume:79 Page:533-549
ISSN:1435-9529
Container-title:Bulletin of Engineering Geology and the Environment
language:en
Short-container-title:Bull Eng Geol Environ

Author:

Sun Xiaohui,Chen Jianping,Han Xudong,Bao Yiding,Zhan Jiewei,Peng Wei

Funder

Key Project of NSFC-Yunnan Joint Fund

State Key Program of National Natural Science Foundation of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation Funded Project

Graduate Innovation Fund of Jilin University

Publisher

Springer Science and Business Media LLC

Subject

Geology,Geotechnical Engineering and Engineering Geology

Link

http://link.springer.com/content/pdf/10.1007/s10064-019-01572-5.pdf

Reference62 articles.

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2. Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31. https://doi.org/10.1016/j.geomorph.2004.06.010

3. Bai S-B, Wang J, Lue G-N, Zhou P-G, Hou S-S, Xu S-N (2010) GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the three gorges area, China. Geomorphology 115:23–31. https://doi.org/10.1016/j.geomorph.2009.09.025

4. Ballabio C, Sterlacchini S (2012) Support vector Machines for Landslide Susceptibility Mapping: the Staffora River basin case study, Italy. Math Geosci 44:47–70. https://doi.org/10.1007/s11004-011-9379-9

5. Binh Thai P, Dieu Tien B, Dholakia MB, Prakash I, Ha Viet P, Mehmood K, Hung Quoc L (2017a) A novel ensemble classifier of rotation forest and naive Bayer for landslide susceptibility assessment at the Luc yen district, Yen Bai Province (Viet Nam) using GIS. Geomatics Nat Hazards Risk 8:649–671. https://doi.org/10.1080/19475705.2016.1255667

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