GIS-Based and Data-Driven Bivariate Landslide-Susceptibility Mapping in the Three Gorges Area, China

摘要

A detailed landslide-susceptibility map was produced using a data-driven objective bivariate analysis 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 because of the frequency and distribution of landslides. The site covered an area of 260,93 km(2) with a landslide area of 5.32 km2. Four data domains were used in this study, including remote sensing products, thematic maps, geological maps, and topographical maps, all with 25 in x 25 m pixels. Statistical relationships for landslide susceptibility were developed using landslide and landslide causative factor databases. All continuous variables were converted to categorical variables according to the percentile divisions of seed cells, and the corresponding class weight values were calculated and summed to create the susceptibility map. According to the map, 3.6% of the study area was identified as high-susceptibility. Extremely low-, very low-, low-, and medium-susceptibility zones covered 19.66%, 31.69%, 27.95%, and 17.1% of the area, respectively. The high- and medium-hazardous zones are along both sides of the Yangtze River, being in agreement with the actual distribution of landslides.