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Zhou Qingjie, Li Xishuang, Xu Yuanqin, Liu Lejun, Gao Shan, Zhou Hang, Li Tianguang. A rapid method to recognize submarine landslides based on the principle of water depth gradient: A case of Baiyun deep-water area, north slope of the South China Sea[J]. Haiyang Xuebao, 2017, 39(1): 138-147. doi: 10.3969/j.issn.0253-4193.2017.01.015
Citation: Zhou Qingjie, Li Xishuang, Xu Yuanqin, Liu Lejun, Gao Shan, Zhou Hang, Li Tianguang. A rapid method to recognize submarine landslides based on the principle of water depth gradient: A case of Baiyun deep-water area, north slope of the South China Sea[J]. Haiyang Xuebao, 2017, 39(1): 138-147. doi: 10.3969/j.issn.0253-4193.2017.01.015

A rapid method to recognize submarine landslides based on the principle of water depth gradient: A case of Baiyun deep-water area, north slope of the South China Sea

doi: 10.3969/j.issn.0253-4193.2017.01.015
  • Received Date: 2016-05-17
  • Rev Recd Date: 2016-07-07
  • How to recognize submarine landslides and quickly and accurately obtain their geometric information is the key issue concerned in marine engineering geology, especially in the deep-water sea. According to the terrain morphology formed after landsliding, we proposed in this paper a rapid method to recognize the submarine landslides based on the principle of water depth gradient and programmed using Matlab to conduct the calculation. As a case of the Baiyun deep-water area, north slope of the South China Sea, we recognized marine landslides using the proposed method. Some of these landslides were verified in sub-bottom profiles suggesting the feasibility of the new method. This approch can recognize submarine landslides automatically, so it is efficient and suitable for small landslides with numerous amount. Two factors are shown to influence the recognition result. One is the threshold value in calculation which can be determined through testing in combination with geophysical data, i.e. Sub-bottom profile and sonic image, and the other is the spatial resolution of water depth. A reasonable spatial resolution will be helpful to improve the accuracy of the recognition result.
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