Spatial distribution and susceptibility zoning of geohazards along the Silk Road, Xian-Lanzhou

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• 作者：Jianqi Zhuang ; Jianbing Peng ; Xinghua Zhu ; Wei Li…
• 关键词：Geohazards ; Spatial distribution ; Susceptibility zoning ; Xi’an to Lanzhou ; Silk Road
• 刊名：Environmental Earth Sciences
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：75
• 期：8
• 全文大小：12,451 KB
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• 作者单位：Jianqi Zhuang (1) (2) (3)
  Jianbing Peng (1) (2)
  Xinghua Zhu (1)
  Wei Li (1)
  Penghui Ma (1)
  Tieming Liu (1)
  
  1. Key Laboratory of Western China Mineral Resources and Geological Engineering, College of Geological Engineering and Surveying, Chang’an University, Xi’an, 710054, China
  2. The Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
  3. State Key Laboratory of Geohazard Prevention and Geoenvrionment Protection, Collaborative Innovation Center of Geological Prevention, Chengdu, 610041, China
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：None Assigned
• 出版者：Springer Berlin Heidelberg
• ISSN：1866-6299

文摘

The region between Xi’an and Lanzhou is the first and most important part of the so-called Silk Road in China. However, this section is highly susceptible to geohazards, including landslides, debris flows, etc., as a result of complex geological formations, steep landforms, seasonal heavy rainfall, and intensive anthropogenic activity that characterize this region. These geohazards have resulted in significant damage to the local infrastructure and economy and are becoming increasingly frequent with time. To identify the distribution of characteristics of geohazards and susceptibility zoning in this region, a frequency analysis and logistic analysis were used to study the spatial distribution of geohazards. The key factors of surface topography and geology associated with geohazards were considered, including slope gradient, height differential, profile curvature, slope aspect, and rock hardness. First, the distribution and frequency of geohazards were discussed in relation to the five factors. Second, each factor’s influence was evaluated by logistic regression and the relative importance of each of the variables was discussed. Finally, geohazard susceptibility zoning was mapped using logistic regression and geography information system tools. The results of the susceptibility zoning model were validated using the locations that had recorded geohazards in recent decades; the accuracy of the model was greater than 86.8 %. The model validation proved that there was good agreement between the susceptibility mapping and historically recorded geohazards. The logistic regression model produced acceptable results using a receiver operating characteristics curve in which the total area under the receiver operating characteristics curve was 0.879. The results of this study can assist in preliminary planning for land use, particularly with reference to construction projects in high risk areas.