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南海区域商船典型空间分布及贸易流向研究
引用本文:梅强,吴琳,彭澎,周鹏,陈金海.南海区域商船典型空间分布及贸易流向研究[J].地球信息科学,2018,20(5):632-639.
作者姓名:梅强  吴琳  彭澎  周鹏  陈金海
作者单位:1. 集美大学航海学院,厦门 3610212. 船舶辅助导航技术国家地方联合工程研究中心, 厦门 3610213. 中国科学院计算技术研究所,北京 1001904. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京100101
基金项目:国家自然科学基金项目(41501490);中国科学院重点部署项目(ZDRW-ZS-2016-6-3);福建省教育厅基金(JAT160257);福建省教育厅教改项目(JZ160302);集美大学李尚大基金(ZC2016005)
摘    要:随着中国对外开放的深入以及“一带一路”倡议的推进,南海战略地位更加显著。如何科学监管南海船舶,维护国家权益,促进地区之间贸易也成为摆在政府部门面前的难题。在本文中利用南海区域2015年的卫星AIS数据与船舶数据档案资料,通过计算南海水域船舶交通密度分析主要航路,与关键门线船舶流量计算相结合,明确船舶典型空间分布;同时基于4种类型船舶的主要航路的选择,明确南海货物贸易主要流向。研究成果表明:① 船舶空间分布在《世界大洋航路》的推荐航线上,南海的建设开发并未影响船舶的贸易运输;② 贸易运输以跨越南海的长距离运输为主,珠三角作为主要航路的重要端点表明中国在南海贸易的优势地位。

关 键 词:AIS  南海  交通密度分析  门线计算  贸易流向  一带一路  
收稿时间:2017-12-28

Typical Spatial Distribution of Merchant Vessels and Trade Flow in South China Sea
MEI Qiang,WU Lin,PENG Peng,ZHOU Peng,CHEN Jinhai.Typical Spatial Distribution of Merchant Vessels and Trade Flow in South China Sea[J].Geo-information Science,2018,20(5):632-639.
Authors:MEI Qiang  WU Lin  PENG Peng  ZHOU Peng  CHEN Jinhai
Institution:1. Navigation college, Jimei University, Xiamen 361021, China2. National-local Joint Engineering Research Center for Marine Navigation Aids Services, Xiamen 36102, China3. Institute of computing technology, Chinese Academy of Sciences, Beijing 100190, China4. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China
Abstract:With the deepening of China's opening to the outside world and the advancement of the Belt and Road Initiative, South China Sea, as an important gateway to China's opening-up and a vital joint for important sea-routes gathering in the world, is embodying prominently strategic position. How to ensure the safety of routes and regulate the vessels sailing in the open water of the south China Sea, safeguard national rights and enhance regional trade is a difficult problem for governmental administrators. In this paper, we excavated the typical spatial distribution of vessels by calculating and visualizing the traffic density of navigation in the South China Sea to analyze the main routes selected by full use of the satellite AIS data of South China sea in 2015 and vessel information database, so the habitual routes could be detected in this region. On the other hand, the statistics on the number of vessels in South China Sea were computed by the statistic line set to find the peak points of the vessel crossing data on the main routes being selected by the most of vessels. Via the above steps, the typical spatial distribution of vessels was defined clearly. Meanwhile, the main flow of trades in South China Sea was determined based on 4 dominant sorts (Bulk, Container, Oil&Chemical and Ro-Ro) of vessels' main routes selected. Research indicated that: (1) The main routes followed the authoritative sailing book《Admiralty Ocean Passage for the World》, which provides sailors with the routes consisting of the waypoints recommended. As a result, the construction and development have little influence on the navigation in this region. Maritime safety administrator can set traffic separation scheme efficiently based on this research; (2) Long-distance shipping is the major mode of transportation. Pearl River Delta being one of the main ends of trade flow indicates the China's dominant position in the South China Sea Trade. This research also attracts more attention to the Beibu Gulf and Hainan Island’s trade potentiality.
Keywords:Automatic Identification System  South China Sea  traffic density analysis  statistics lines calculation  trade flow  the Belt and Road Initiatives  
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