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Analysis of global marine oil trade based on automatic identification system (AIS) data

机译:基于自动识别系统(AIS)数据的全球海洋石油贸易分析

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摘要

A fine-grained analysis framework of global marine oil trade based on AIS data is developed to address the existing problems of using statistical data to analyze oil trade without sufficient temporal and spatial resolution. The framework includes three modules: traffic route analysis, trade volume analysis, and trade network analysis. A ship cargo payload calculation (SCPC) model is proposed to take the draught, shape, and size of the vessel and seawater density into consideration. It calculates the oil trade volume of each oil tanker voyage as a unit. More than 3.4 billion global automatic identification system (AIS) records in 2017 are utilized to verify the proposed framework and achieve the following findings. The Middle East-Strait of Malacca-East Asia oil transport route is the busiest and largest trade volume route in the global marine oil trade. The oil trade volume of the world's top 20 oil-importing and oil-exporting countries calculated based on AIS data is strongly correlated to the Joint Organizations Data Initiative (JODI) statistics with the determination coefficient (R-2) of 0.8798. More than 90% of the world's top 20 oil-importing and oil-exporting countries have more than five oil trading partners. The experimental results show that the proposed analysis framework has utilized the most minimal research object, every oil tanker's trajectory, to realize the fine-grained research of marine oil trade based on oil tanker flows analysis. The derived oil flows with directions and trade volumes provide the basis for constructing a directed weighted oil trade network.
机译:建立了基于AIS数据的全球海洋石油贸易细粒度分析框架,以解决使用统计数据分析石油贸易而没有足够的时空分辨率的现有问题。该框架包括三个模块:交通路线分析,贸易量分析和贸易网络分析。提出了一种船舶货物有效载荷计算(SCPC)模型,以考虑船舶的吃水深度,形状和大小以及海水密度。它以单位为单位计算每个油轮航行的石油交易量。 2017年,超过34亿个全球自动识别系统(AIS)记录用于验证拟议的框架并实现以下发现。马六甲-东亚中东海峡的石油运输路线是全球海洋石油贸易中最繁忙,贸易量最大的路线。根据AIS数据计算出的世界前20个石油进口和出口国家的石油贸易量与联合组织数据倡议(JODI)的统计数据密切相关,其确定系数(R-2)为0.8798。在世界20大石油进口和出口国家中,超过90%的国家拥有超过5个石油贸易伙伴。实验结果表明,所提出的分析框架利用了最少的研究对象,即每个油轮的轨迹,基于油轮流量分析实现了海洋石油贸易的细粒度研究。导出的具有方向和交易量的石油流为构建定向加权石油贸易网络提供了基础。

著录项

  • 来源
    《Journal of Transport Geography》 |2020年第2期|102637.1-102637.15|共15页
  • 作者

  • 作者单位

    Nanjing Univ Sch Geog & Ocean Sci Nanjing 210023 Peoples R China|Nanjing Univ Collaborat Innovat Ctr South Sea Studies Nanjing 210093 Peoples R China|Nanjing Univ Jiangsu Prov Key Lab Geog Informat Sci & Technol Nanjing 210093 Peoples R China|Univ Wisconsin Dept Civil & Environm Engn Madison WI 53706 USA|163 Xianlin Rd Nanjing 210023 Jiangsu Peoples R China;

    Nanjing Univ Sch Geog & Ocean Sci Nanjing 210023 Peoples R China|Nanjing Univ Collaborat Innovat Ctr South Sea Studies Nanjing 210093 Peoples R China|163 Xianlin Rd Nanjing 210023 Jiangsu Peoples R China;

    Nanjing Univ Sch Geog & Ocean Sci Nanjing 210023 Peoples R China|Nanjing Univ Collaborat Innovat Ctr South Sea Studies Nanjing 210093 Peoples R China|Nanjing Univ Jiangsu Prov Key Lab Geog Informat Sci & Technol Nanjing 210093 Peoples R China|Nanjing Univ Collaborat Innovat Ctr Novel Software Technol & I Nanjing 210023 Peoples R China;

    Nanjing Univ Sch Geog & Ocean Sci Nanjing 210023 Peoples R China|Nanjing Univ Collaborat Innovat Ctr South Sea Studies Nanjing 210093 Peoples R China|Nanjing Univ Jiangsu Prov Key Lab Geog Informat Sci & Technol Nanjing 210093 Peoples R China|163 Xianlin Rd Nanjing 210023 Jiangsu Peoples R China;

    Santa Clara Univ Dept Civil Environm & Sustainable Engn Santa Clara CA 95053 USA|500 EI Camino Real Santa Clara CA 95053 USA;

    Univ Wisconsin Dept Civil & Environm Engn Madison WI 53706 USA|2312 Engn Hall 1415 Engn Dr Madison WI 53706 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Oil trade; AIS data; Ship traffic; Route analysis; Trade volume calculation;

    机译:石油贸易;AIS数据;船舶交通;路线分析;交易量计算;

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