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  2. 烟台海岸带研究所
  3. 中国科学院烟台海岸带研究所
  4. 中科院海岸带环境过程与生态修复重点实验室
  5. 海岸带信息集成与综合管理实验室
A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities

文献类型：期刊论文

作者Liu, Baijing3,4; Gong, Meng2; Wu, Xiaoqing1,4; Liu, Xin4
刊名SUSTAINABLE CITIES AND SOCIETY
出版日期2021-09-01
卷号72页码:10
关键词Vessel anchoring pressure Automatic identification system Machine learning Illegal anchoring area Sustainable marine management
ISSN号2210-6707
DOI10.1016/j.scs.2021.103011
通讯作者Wu, Xiaoqing(xiaoqingwuyic@163.com) ; Liu, Xin(xliu@yic.ac.cn)
英文摘要The increased utilization of marine areas represents a significant challenge to the sustainable eco-environmental management of coastal cities. Machine learning, specifically the support-vector machine classification algorithm, was used to preprocess the massive Automatic identification System (AIS) dataset and extract anchoring vessels. Then, a comprehensive indicator evaluation model for anchoring pressure (CAPI) was constructed to evaluate the potential marine ecological pressure associated with anchoring vessels in the Bohai Sea. Spatial analysis was performed by geographic information system (GIS) to identify improper anchoring areas with high CAPI values. Finally, anchorage management in various coastal cities was assessed. The results showed that: (1) machine learning technology accurately identified anchoring vessels, (2) improper anchoring in the Bohai Sea is common, and (3) the management of anchoring activities is generally poor at boundaries between administrative regions. This study provides a rapid, feasible, and effective visualization method for marine environmental managers both theoretically and practically. The data mining method and CAPI model proposed here facilitate the management of vessel-related social issues in coastal cities, and they will help decision makers to quickly formulate targeted management measures to support the sustainable economic and environmental development of coastal cities.
WOS关键词AIS DATA ; INDICATORS ; STRESSORS ; SEAGRASS ; IMPACTS ; SCIENCE
资助项目National Key R&D Program of China[2019YFD0900705] ; Shandong Provincial Natural Science Foundation[ZR2020MD014]
WOS研究方向Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels
语种英语
WOS记录号WOS:000672607600003
资助机构National Key R&D Program of China ; Shandong Provincial Natural Science Foundation
源URL[http://ir.yic.ac.cn/handle/133337/29476]  
专题烟台海岸带研究所_海岸带信息集成与综合管理实验室
烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室
通讯作者Wu, Xiaoqing; Liu, Xin
作者单位1.Chinese Acad Sci, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
2.Prov Geomat Ctr Jiangsu, Nanjing 210013, Jiangsu, Peoples R China
3.Univ Chinese Acad Sci, Beijing 101400, Peoples R China
4.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Baijing,Gong, Meng,Wu, Xiaoqing,et al. A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities[J]. SUSTAINABLE CITIES AND SOCIETY,2021,72:10.
APA Liu, Baijing,Gong, Meng,Wu, Xiaoqing,&Liu, Xin.(2021).A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities.SUSTAINABLE CITIES AND SOCIETY,72,10.
MLA Liu, Baijing,et al."A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities".SUSTAINABLE CITIES AND SOCIETY 72(2021):10.

入库方式： OAI收割

来源：烟台海岸带研究所

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