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

作　　者：BAI Shi-Biao WANG Jian LU Guo-Nian ZHOU Ping-Gen HOU Sheng-Shan XU Su-Ning 

机构地区：[1]College of Geography Science, Nanjing Normal University, Nanjing 210097 （China） [2]China Institute of Geo-Environment Monitoring, Beijing 100081 （China）

出　　处：《Pedosphere》2009年第1期14-20,共7页土壤圈（英文版）

基　　金：supported by the National Natural Science Foundation of China (Nos.40801212 and 49971064);the Foun-dation for China Geological Survey (No.200316000035);the Natural Science Foundation of Jiangsu Higher Education Institutions of China (No.06KJB170063);the Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection of Chendu University of Technology, China (No.GZ2007-11).

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 km^2. Four data domains were used in this study, including remote sensing products, thematic maps, geological maps, and topographical maps, all with 25 m × 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-hazardons zones are along both sides of the Yangtze River, being in agreement with the actual distribution of landslides.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 km2 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 m × 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.

关 键 词：causative factors landslide-susceptibility statistical approaches Three Gorges area 

分 类 号：P942[天文地球—自然地理学]