AIMS Geosciences, 2017, 3(1): 116-141. doi: 10.3934/geosci.2017.1.116 Research article

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Landslide Susceptibility Mapping Using GIS-based Vector Grid File (VGF) Validating with InSAR Techniques: Three Gorges, Yangtze River (China)

Cem Kıncal, Zhenhong Li, Jane Drummond, Peng Liu, Trevor Hoey, Jan-Peter Muller

1 Geological Engineering Department, Engineering Faculty, Dokuz Eylül University, Izmir, Turkey
2 School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, UK
3 School of Geographical and Earth Sciences, University of Glasgow, Glasgow G12 8QQ, UK
4 Southern University of Science and Technology, Nanshan District, Shenzhen, Guangdong, China
5 Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, UK

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A landslide susceptibility assessment for the Three Gorges (TG) region (China) was performed in a Geographical Information System (GIS) environment and Persistent Scatterer (PS) InSAR derived displacements were used for validation purposes. Badong County of TG was chosen as case study field. Landslide parameters were derived from two datasets. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM) was used to calculate slope geometry parameters (slope, aspect, drainage, and lineament), while geology and vegetation cover were obtained from Landsat and ASTER data. The majority of historical landslides occurred in the sandstone-shale-claystone intercalations. It appears that slope gradients are more critical than other parameters such as aspect and drainage. The susceptibility assessment was based on a summation of assigned susceptibility scores (points) for each 30×30 m unit in a database of a Vector Grid File (VGF) composed of ‘vector pixels’. A landslide susceptibility map (LSM) was generated using VGF and classified with low, moderate and high landslide susceptibility zones. The comparison between the LSM and PS InSAR derived displacements suggests that landslides only account for parts of the observed surface movements.

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Copyright Info: © 2017, Cem Kıncal, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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