Chapter 11
Modelling Shallow Landslide Risk Using GIS
and a Distributed Hydro-geotechnical Model
Pingping Luo, Apip, Bin He, Kaoru Takara, Weili Duan, Maochuan Hu,
and Daniel Nover
Abstract GIS and distributed hydrological models are important tools for shallow
landslide prediction, particularly as such disasters are exacerbated by global change
driven changes in precipitation regimes. The main objective of this chapter is to
outline a detailed methodology for shallow landslide risk assessment using GIS and
a hydrological model. We have developed a method to assess shallow landslide risk
using GIS tools and a distributed hydrological model and further used this method
to analyze the probability of shallow landslides in a case study. The physically
P. Luo (*)
Institute for the Advanced Study of Sustainability (UNU-IAS), United Nations University,
Shibuya, Tokyo, Japan
Disaster Prevention Research Institute (DPRI), Kyoto University, Uji, Kyoto, Japan
e-mail: luoping198121@gmail.com
Apip
Research Centre for Limnology, Indonesian Institute of Sciences (LIPI), Cibinong, Indonesia
e-mail: apip@limnologi.lipi.go.id
B. He (*) • W. Duan
CAS Key Laboratory of Watershed Geographic Sciences, Chinese Academy of Sciences,
Nanjing Institute of Geography and Limnology, Nanjing, China
e-mail: hebin@niglas.ac.cn; wlduan@nislas.ac.cn
K. Takara
Disaster Prevention Research Institute (DPRI), Kyoto University, Uji, Kyoto, Japan
e-mail: takara.kaoru.7v@kyoto-u.ac.jp
M. Hu (*)
Department of Civil and Earth Resources Engineering, Graduate School of Engineering,
Kyoto University, Kyoto daigaku-Kastura, Nishikyo-ku, Kyoto 615-8530, Japan
e-mail: hu-maochuan@163.com
D. Nover
Global Change Research Program, U.S. Environmental Protection Agency,
Washington, DC, USA
e-mail: dmnover@gmail.com
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_11
221
Modelling Shallow Landslide Risk Using GIS
and a Distributed Hydro-geotechnical Model
Pingping Luo, Apip, Bin He, Kaoru Takara, Weili Duan, Maochuan Hu,
and Daniel Nover
Abstract GIS and distributed hydrological models are important tools for shallow
landslide prediction, particularly as such disasters are exacerbated by global change
driven changes in precipitation regimes. The main objective of this chapter is to
outline a detailed methodology for shallow landslide risk assessment using GIS and
a hydrological model. We have developed a method to assess shallow landslide risk
using GIS tools and a distributed hydrological model and further used this method
to analyze the probability of shallow landslides in a case study. The physically
P. Luo (*)
Institute for the Advanced Study of Sustainability (UNU-IAS), United Nations University,
Shibuya, Tokyo, Japan
Disaster Prevention Research Institute (DPRI), Kyoto University, Uji, Kyoto, Japan
e-mail: luoping198121@gmail.com
Apip
Research Centre for Limnology, Indonesian Institute of Sciences (LIPI), Cibinong, Indonesia
e-mail: apip@limnologi.lipi.go.id
B. He (*) • W. Duan
CAS Key Laboratory of Watershed Geographic Sciences, Chinese Academy of Sciences,
Nanjing Institute of Geography and Limnology, Nanjing, China
e-mail: hebin@niglas.ac.cn; wlduan@nislas.ac.cn
K. Takara
Disaster Prevention Research Institute (DPRI), Kyoto University, Uji, Kyoto, Japan
e-mail: takara.kaoru.7v@kyoto-u.ac.jp
M. Hu (*)
Department of Civil and Earth Resources Engineering, Graduate School of Engineering,
Kyoto University, Kyoto daigaku-Kastura, Nishikyo-ku, Kyoto 615-8530, Japan
e-mail: hu-maochuan@163.com
D. Nover
Global Change Research Program, U.S. Environmental Protection Agency,
Washington, DC, USA
e-mail: dmnover@gmail.com
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_11
221