{"title":"基于卫星AIS数据的南海交通信息态势挖掘与分析","authors":"Tianyu Pu","doi":"10.4018/ijdwm.332864","DOIUrl":null,"url":null,"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.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":"48 7","pages":"0"},"PeriodicalIF":0.5000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mining and Analysis of the Traffic Information Situation in the South China Sea Based on Satellite AIS Data\",\"authors\":\"Tianyu Pu\",\"doi\":\"10.4018/ijdwm.332864\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":54963,\"journal\":{\"name\":\"International Journal of Data Warehousing and Mining\",\"volume\":\"48 7\",\"pages\":\"0\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Warehousing and Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijdwm.332864\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Warehousing and Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijdwm.332864","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Mining and Analysis of the Traffic Information Situation in the South China Sea Based on Satellite AIS Data
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.
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