| 一种基于水深梯度原理的海底滑坡快速识别方法——以南海北部陆坡白云深水区为例 |
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| 引用本文： | 周庆杰,李西双,徐元芹,刘乐军,高珊,周航,李天光.一种基于水深梯度原理的海底滑坡快速识别方法——以南海北部陆坡白云深水区为例[J].海洋学报,2017,39(1):138-147. |
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| 作者姓名： | 周庆杰 李西双 徐元芹 刘乐军 高珊 周航 李天光 |
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| 作者单位： | 1.国家海洋局第一海洋研究所 海洋沉积与环境地质国家海洋局重点实验室, 山东 青岛 266061;青岛海洋科学与技术国家实验室 海洋地质过程与环境功能实验室, 山东 青岛 266061 |
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| 基金项目： | 基本科研业务费专项资金——近50年来广西大陆岸线变迁及其与人类活动的关系（2014G05）；国家自然科学基金——南海北部陆坡峡谷区海底滑坡体的识别与年代界定研究（41506071）；国家重大科技专项——荔湾3-1及周边气田地质灾害风险评价研究（2011ZX05056-001-02）。 |
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| 摘 要： | 如何快速而准确的识别并提取海底滑坡的特征形态信息一直是海洋工程地质、特别是深水工程地质评价中所关注的问题之一。本文根据滑坡后形成的地形形态，基于水深梯度求值运算的原理，通过Matlab编程建立了一种快速识别海底滑坡的方法。以南海北部陆坡白云深水区为例进行海底滑坡的识别，并利用浅地层剖面做验证，结果显示这一方法是可行的，其最大的优点是滑坡识别速度快，对于规模小且数量多的滑坡识别效率较高。通过实测数据进一步的分析表明:（1）阈值的选取对识别结果有明显影响，阈值的选取需要结合其他物探资料（如浅地层剖面和声呐影像）综合判断来确定；（2）水深数据的空间分辨率会影响滑坡识别结果的准确度，合适的空间分辨率会提高识别结果的准确性。
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| 关 键 词： | 南海北部陆坡 海底滑坡 水深梯度 阈值 |
| 收稿时间： | 2016/5/17 0:00:00 |
| 修稿时间： | 7/7/2016 12:00:00 AM |
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 |
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| Zhou Qingjie,Li Xishuang,Xu Yuanqin,Liu Lejun,Gao Shan,Zhou Hang and 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].Acta Oceanologica Sinica (in Chinese),2017,39(1):138-147. |
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| Authors: | Zhou Qingjie Li Xishuang Xu Yuanqin Liu Lejun Gao Shan Zhou Hang and Li Tianguang |
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| Institution: | Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China,Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China,Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China,Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China,Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China,Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China and Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China |
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| Abstract: | 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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| Keywords: | north of the South China Sea submarine landslides water depth gradient threshold value |
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