Mining and Analysis of the Traffic Information Situation in the South China Sea Based on Satellite AIS Data

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Tianyu Pu
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引用次数: 0

Abstract

The loading of Automatic Identification System equipment on low-orbiting satellites can adapt to the demand of exchanging data and information with greater “capacity” brought by the AIS data information of ships in deep waters that cannot be covered by land-based stations. The information in the satellite AIS data contains a large number of potential features of ship activities, and by selecting the ship satellite AIS data of typical months in the South China Sea in 2020. Data mining, geographic information system, and traffic flow theory are used to visualize and analyze the ship activities in the South China Sea. The study shows that the distribution of ship routes in the South China Sea is highly compatible with the recommended routes of merchant ships, and the width of the track belt is obviously characterized. The number of ships passing through the southern waters of the Taiwan Strait has increased significantly, and the focus of traffic safety in the South China Sea should also focus on major route belt and important straits.
基于卫星AIS数据的南海交通信息态势挖掘与分析
在低轨卫星上装载自动识别系统设备,可以适应陆基台站无法覆盖的深海船舶AIS数据信息带来的更大“容量”的数据信息交换需求。卫星AIS数据中的信息包含大量船舶活动的潜在特征,通过选取2020年南海典型月份的船舶卫星AIS数据。运用数据挖掘、地理信息系统和交通流理论对南海海域船舶活动进行可视化分析。研究表明,南海船舶航路分布与商船推荐航路高度契合,航路带宽度特征明显。通过台湾海峡南部海域的船舶数量明显增加,南海交通安全的重点也应集中在主要航路带和重要海峡。
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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