Landslide Susceptibility Modeling

Hiromitsu Yamagishi is a graduate of Faculty of Geology and Mineralogy, Hokkaido University, Japan. He has been actively involved in geological mapping and surveying in Japan for more than 35 years. Dr. Yamagishi currently works as an Executive Member of Hokkaido Research Center of Geology (HRCG), Japan. Formerly, he served as Director of two research institutes: Center of Geographical Information Center, Niigata University, and Disaster Division of Center for Disaster Management Informatics Research, Ehime University. He also served as President of Landslide Society of Japan (2004-2006). Dr. Yamagishi has co-authored several books and journal articles. Jie Dou is an expert in computer assisted landslide mapping. He completed his Ph.D from The University of Tokyo, in the laboratory of Centre for Spatial Information Science (CSIS). He published several papers on machine learning techniques in landslide susceptibility mapping and modelling. Dr Dou previously served as a visiting researcher in the CSIS and a research scientist at Public Work Research Institute, Tsukuba, Japan, respectively. He is also the recipient of the prestigious JSPS fellowship, and currently working in Department of Civil and Environmental Engineering, Nagaoka University of Technology, Japan. Dr. Dou has published over 50 peer-reviewed papers, and cited over 600 times. He is also serving as a reviewer for over 20 international SCI journals. Ali. P Yunus has been working in the field of geomorphology and landslide hazard analysis for the last 10 years. He graduated from The University of Tokyo, worked as postdoc in the Uni. of Tokyo and currently working at State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Sichuan, China. Currently he is focusing on post-seismic landslide controls and evolution. Previously, he served as an assistant professor at Department of Geology, Aligarh Muslim University, India. He published several research papers in remote sensing and GIS related research in peer reviewed international journals.

1. Landslide hazards, risks and mitigation
2. Landslide inventory mapping - Past and Current Trends
3. Landslide controlling factors
4. Data and Tools in LSM
5. Landslide types and failure mechanism
6. Evolving controls of landslides
7. Case studies – (a) Landslide susceptibility mapping using knowledge driven methods
8. Case studies – (b) Landslide susceptibility mapping using statistical models
9. Case studies – (c) Landslide susceptibility mapping using machine learning models
10. Case studies – (d) Landslide susceptibility with deep learning
11. Accuracy assessments of susceptibility maps
12. Challenges and Recommendations