| A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities | |
Liu, Baijing1,2; Gong, Meng3; Wu, Xiaoqing1,4 ; Liu, Xin1
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| Source Publication | SUSTAINABLE CITIES AND SOCIETY
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| ISSN | 2210-6707 |
| 2021-09-01 | |
| Volume | 72Pages:10 |
| Keyword | Vessel anchoring pressure Automatic identification system Machine learning Illegal anchoring area Sustainable marine management |
| DOI | 10.1016/j.scs.2021.103011 |
| Corresponding Author | Wu, Xiaoqing(xiaoqingwuyic@163.com) ; Liu, Xin(xliu@yic.ac.cn) |
| Abstract | 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. |
| Funding Organization | National Key R&D Program of China ; Shandong Provincial Natural Science Foundation |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | AIS DATA ; INDICATORS ; STRESSORS ; SEAGRASS ; IMPACTS ; SCIENCE |
| WOS Research Area | Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels |
| WOS ID | WOS:000672607600003 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.yic.ac.cn/handle/133337/29477 |
| Collection | 中科院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心 中科院海岸带环境过程与生态修复重点实验室 |
| Corresponding Author | Wu, Xiaoqing; Liu, Xin |
| Affiliation | 1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101400, Peoples R China 3.Prov Geomat Ctr Jiangsu, Nanjing 210013, Jiangsu, Peoples R China 4.Chinese Acad Sci, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China |
| Recommended Citation 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. |
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| A comprehensive mode（7810KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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