A comprehensive model of vessel anchoring pressure based on machine learning to support the sustainable management of the marine environments of coastal cities

doi:10.1016/j.scs.2021.103011

CORC > 烟台海岸带研究所 > 中国科学院烟台海岸带研究所 > 中科院海岸带环境过程与生态修复重点实验室 > 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
	Liu, Baijing 1,2; Gong, Meng 3; Wu, Xiaoqing 1,4; Liu, Xin 1
刊名	SUSTAINABLE CITIES AND SOCIETY
	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
DOI	10.1016/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.
资助项目	National Key R&D Program of China[2019YFD0900705] ; Shandong Provincial Natural Science Foundation[ZR2020MD014]
WOS关键词	AIS DATA ; INDICATORS ; STRESSORS ; SEAGRASS ; IMPACTS ; SCIENCE
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
内容类型	期刊论文
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, 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
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.