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The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling
Authors:Chong Xu  Xiwei Xu  Yuan Hsi Lee  Xibin Tan  Guihua Yu  Fuchu Dai
Institution:(1) Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing, 100029, People’s Republic of China;(2) Department of Earth and Environmental Sciences, National Chung-Cheng University, Chiayi, 62102, Taiwan, ROC;(3) Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, People’s Republic of China
Abstract:The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.
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