GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area, China

A detailed landslide susceptibility map was produced using a logistic regression method with datasets developed for a geographic information system (GIS). Known as one of the most landslide-prone areas in China, the Zhongxian–Shizhu segment in the Three Gorges Reservoir region of China was selected as a suitable case to evaluate the frequency and distribution of landslides. The site covered an area of 260.9 km2 with a landslide area of 5.3 km2. Four data domains were used in this study: remote sensing products, thematic maps, geological maps, and topographical maps, all with 25 × 25 m2 pixels or cells. Statistical relationships for landslide susceptibility were developed using landslide and landslide causative factor databases. We extended the application of logistic regression approaches to use all continuous variables as they are, and the landslide density is used to transform these nominal variables to numeric variable. According to the map, 2.8% of the study area was identified as an area with very high-susceptibility, whereas very low-, low-, medium- and high-susceptibility zones covered 18.2%, 36.2%, 26.7%, and 16.1% of the area, respectively. The quality of susceptibility mapping was validated, and the correct classification percentage and root mean square error (RMSE) values for the validation data were 81.4% and 0.392, respectively.