基于GIS和AIS的渤海海上船舶活动时空特征分析

doi:10.18306/dlkxjz.2020.07.010

地理科学进展 ›› 2020, Vol. 39 ›› Issue (7): 1172-1181.doi: 10.18306/dlkxjz.2020.07.010

基于GIS和AIS的渤海海上船舶活动时空特征分析

陈仁丽¹^,²(), 王宜强³, 刘柏静¹^,², 宫萌¹^,², 吴晓青¹^,⁴^,^*()

1. 中国科学院烟台海岸带研究所,山东烟台 264003
2. 中国科学院大学,北京 100049
3. 曲阜师范大学地理与旅游学院,山东日照 276826
4. 中国科学院海岸带环境过程与生态修复重点实验室,山东烟台 264003

收稿日期:2019-05-13 修回日期:2019-07-27 出版日期:2020-07-28 发布日期:2020-09-28
通讯作者: 吴晓青
作者简介:陈仁丽(1996— ),女,山东潍坊人,硕士生,研究方向为GIS与遥感应用。E-mail: 1987887320@qq.com
基金资助:
中国科学院重点部署项目(KZZD-EW-14);中国科学院战略性先导科技专项(A类)(XDA11020305);山东省高校人文社科项目(J17RA213)

Spatio-temporal characteristics of ship activities in the Bohai Sea based on GIS and AIS

CHEN Renli¹^,²(), WANG Yiqiang³, LIU Baijing¹^,², GONG Meng¹^,², WU Xiaoqing¹^,⁴^,^*()

1. Yantai Institute of Coastal Zone Research, CAS, Yantai 264003, Shandong, China
2. University of Chinese Academy of Science, Beijing 100049, China
3. College of Geography and Tourism, Qufu Normal University, Rizhao 276826, Shandong, China
4. Key Laboratory of Coastal Environment Processes and Ecological Remediation, CAS, Yantai 264003, Shandong, China

Received:2019-05-13 Revised:2019-07-27 Online:2020-07-28 Published:2020-09-28
Contact: WU Xiaoqing
Supported by:
Key Project of the Chinese Academy of Sciences(KZZD-EW-14);Strategic Priority Research Program of the Chinese Academy of Sciences (Class A)(XDA11020305);Shandong University Humanities and Social Science Project(J17RA213)

摘要/Abstract

摘要：

基于2018年海上船舶自动识别系统(Automatic Identification System, AIS)数据,借助GIS空间分析方法,对渤海海上船舶位置及密度、船舶速度等空间分布特征以及船舶流量日、月和季节变化的时间特征进行分析,得到以下结论：① 渔业船舶多活动于近岸海域,呈团聚状分布;商业船舶多聚集在公共航道区,整体呈带状分布;货船数量占商业船舶总量的78.58%,主要为中型货船,客船与油轮以中小型船舶所占比重相对较大。② 渤海船舶速度以中低速为主,尤其是渔业船舶;较高速度的船舶主要是大中型货船和客船。③ 渔业船舶活动时间和季节变化特征显著,秋季休渔期结束后以及白天工作时间段渔船活动较频繁;与渔业船舶相比,渤海商业船舶活动受季节变化和昼夜交替影响较小。分析发现,渤海交通流密度高,船舶会遇频繁,发生船舶碰撞以及重大污染事故的风险较大;东西向和南北向的海上交通与渔业捕捞作业船舶之间存在较大的海域空间利用冲突,需要引起足够的重视。自然环境与资源条件、沿岸社会经济发展与港口建设、海域管制等因素影响海上船舶时空分布。

关键词: 船舶活动, 时空特征, AIS, GIS, 渤海

Abstract:

In recent years, with the rapid development of marine transportation and port logistics and international trade, the traffic density and flow of ships at sea are increasing, which brings many challenges to the safety of maritime navigation and marine ecological environment. The application of Automatic Identification System (AIS) technology provides a good data source for maritime traffic management and marine spatial planning. Based on the AIS data of the Bohai Sea in 2018 with data quality control and sampling processing, this study analyzed the traffic characteristics of the Bohai Sea. By means of mathematical statistics and Geographic Information System (GIS) spatial analysis, the spatial distribution characteristics such as ship position and density, ship speed and the temporal characteristics of daily, monthly, and seasonal changes of ship flow in the Bohai Sea were analyzed in order to reveal the spatial-temporal variations of ship activities in the Bohai Sea. The influencing factors of the spatio-temporal distribution of maritime ship activities were also discussed. The results show that: 1) Fishing ships were mostly located in the offshore area, which were agglomerated. Commercial ships were mostly gathered in the common area, which were distributed in belts. The number of cargo ships accounted for 78.58% of commercial ships and they were mainly medium-sized cargo ships, and passenger ships and oil tankers were mainly small and medium-sized ships. 2) Speed of the ships was mainly medium and low, especially fishery ships. The ships with higher speed were mainly large and medium-sized freighters and passenger ships. 3) The activity time and seasonal change characteristics of fishery ships were significant, and activities were more frequent after the end of the fishing moratorium and during the daytime. Compared with fishery ships, the activities of commercial ships in the Bohai Sea were less affected by seasonal changes and day and night alternation. It is found that the Bohai Sea traffic flow density was high, ships met frequently, and the risk of ship collision and major pollution accidents increased through the study period. There is a large conflict between the east-west and south-north marine traffic and fishing ships in the utilization of maritime space, and more attention needs to be paid to this conflict. Natural environmental and resource conditions, coastal socioeconomic development and port construction, regulation of the sea, and other factors affect the spatio-temporal distribution of marine ships.

Key words: ship activities, spatio-temporal characteristics, AIS, GIS, Bohai Sea

陈仁丽, 王宜强, 刘柏静, 宫萌, 吴晓青. 基于GIS和AIS的渤海海上船舶活动时空特征分析[J]. 地理科学进展, 2020, 39(7): 1172-1181.

CHEN Renli, WANG Yiqiang, LIU Baijing, GONG Meng, WU Xiaoqing. Spatio-temporal characteristics of ship activities in the Bohai Sea based on GIS and AIS[J]. PROGRESS IN GEOGRAPHY, 2020, 39(7): 1172-1181.

图/表 10

图1

图2

图3

表1

图4

表2

图5

图6

表3

图7

参考文献 33

[1]	刘洋, 裴兆斌, 王悦. 辽宁省海洋服务新业态培育与法律保障研究[J]. 海洋开发与管理, 2019,36(3):28-33.
	[ Liu Yang, Pei Zhaobin, Wang Yue. The cultivation of new business forms and legal guarantee of marine service in Liaoning Province. Ocean Development and Management, 2019,36(3):28-33. ]
[2]	牛佳伟, 林威. 卫星探测AIS的关键技术及其影响[J]. 世界海运, 2015,38(8):32-35.
	[ Niu Jiawei, Lin Wei. The key technology and influence of satellite detecting AIS. World Shipping, 2015,38(8):32-35. ]
[3]	万辉. 老铁山水道船舶交通流的调查与分析[J]. 天津航海, 2010(2):14-15, 41.
	[ Wan Hui. Investigation and analysis of ship traffic flow in Laotieshan watercourse. Navigation of Tianjin, 2010(2):14-15, 41. ]
[4]	Scheepens R, Willems N, Van de Wetering H, et al. Interactive visualization of mulvariate trajectory data with density maps [R]. IEEE Pacific Visualization Symposium, PacificVis 2011. Hong Kong, China, 2011: 147-154.
[5]	朱姣, 刘敬贤, 陈笑, 等. 基于轨迹的内河船舶行为模式挖掘[J]. 交通信息与安全, 2017,35(3):107-116, 132.
	[ Zhu Jiao, Liu Jingxian, Chen Xiao, et al. Behavior pattern mining of inland vessels based on trajectories. Journal of Transport Information and Safety, 2017,35(3):107-116, 132. ]
[6]	刘敬贤, 韩晓宝. 渤海海峡船舶流的调查与分析[J]. 船海工程, 2008(4):95-98.
	[ Liu Jingxian, Han Xiaobao. Survey and analysis of vessel traffic flow in the Bohai strait. Ship and Ocean Engineering, 2008(4):95-98. ]
[7]	刘敬贤, 韩晓宝, 易湘平. 基于排队论的受限航道通过能力计算[J]. 中国航海, 2008(3):261-264, 268.
	[ Liu Jingxian, Han Xiaobao, Yi Xiangping. Capacity analysis of restricted channels based on the queuing theory. Navigation of China, 2008(3):261-264, 268. ]
[8]	刘敬贤, 文元桥. 基于船舶行为特征的港口航道通过能力仿真[J]. 大连海事大学学报, 2009,35(2):31-33, 37.
	[ Liu Jingxian, Wen Yuanqiao. Simulation of waterway transit capacity at harbor based on the ship behavior. Journal of Dalian Maritime University, 2009,35(2):31-33, 37. ]
[9]	刘敬贤, 刘聪, 赵振, 等. 基于船种聚类的航道通过能力量化方法[J]. 交通信息与安全, 2017,35(6):46-53.
	[ Liu Jingxian, Liu Cong, Zhao Zhen, et al. A quantitative method for traffic capacity of channels based on clustering of ship types. Journal of Transport Information and Safety, 2017,35(6):46-53. ]
[10]	Curtis R. A ship collision model for overtaking[J]. Journal of the Operational Research Society, 1986,37(4):397-406. doi: 10.1057/jors.1986.67
[11]	Montewka J, Hinz T, Kujala P, et al. Probability modeling of vessel collisions[J]. Reliability Engineering and System Safety, 2010,95(5):573-589. doi: 10.1016/j.ress.2010.01.009
[12]	Montewka J, Krata P, Kujala P, et al. A model for risk analysis of oil tankers[J]. The Archives of Transport, 2010,12(4):423-445.
[13]	Zhang L Y, Meng Q, Fwa T F. Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters[J]. Transportation Research Part E: Logistics and Transportation Review, 2017,129:1-18. doi: 10.1016/j.tre.2019.06.004
[14]	李连博, 牛佳伟, 刘军坡, 等. 基于AIS数据的海区通航危险度决策模型[J]. 中国航海, 2018,41(3):68-75.
	[ Li Lianbo, Niu Jiawei, Liu Junpo, et al. AIS data-based navigation risk modeling. Navigation of China, 2018,41(3):68-75. ]
[15]	李博, 田闯, 史钊源, 等. 辽宁沿海地区海洋经济增长质量空间特征及影响要素[J]. 地理科学进展, 2019,38(7):1080-1092. doi: 10.18306/dlkxjz.2019.07.012
	[ Li Bo, Tian Chuang, Shi Zhaoyuan, et al. Spatial characteristics and influencing factors of marine economic growth quality in Liaoning coastal areas. Progress in Geography, 2019,38(7):1080-1092. ]
[16]	狄乾斌, 孙阳. 沿海地区海洋经济与社会变迁关联度评价: 以辽宁省为例[J]. 地理科学进展, 2014,33(5):713-720. doi: 10.11820/dlkxjz.2014.05.012
	[ Di Qianbin, Sun Yang. Correlation of marine economy and social change in coastal areas: A case study in Liaoning Province. Progress in Geography, 2014,33(5):713-720. ]
[17]	韩增林, 刘桂春. 人海关系地域系统探讨[J]. 地理科学, 2007,27(6):761-767.
	[ Han Zenglin, Liu Guichun. Evolution of China's regional system of man-sea relation and its mechanism. Scientia Geographica Sinica, 2007,27(6):761-767. ]
[18]	刘天宝, 韩增林, 彭飞. 人海关系地域系统的构成及其研究重点探讨[J]. 地理科学, 2017,37(10):1527-1534. doi: 10.13249/j.cnki.sgs.2017.10.009
	[ Liu Tianbao, Han Zenglin, Peng Fei. The composition and important research issues of human-ocean regional system. Scientia Geographica Sinica, 2017,37(10):1527-1534. ]
[19]	翟伟康, 张建辉. 全国海域使用现状分析及管理对策[J]. 资源科学, 2013,35(2):405-411.
	[ Zhai Weikang, Zhang Jianhui. Analysis of conditions, features and problems of sea area utilization in China. Resources Science, 2013,35(2):405-411. ]
[20]	刘柏静, 贾静, 吴晓青, 等. 基于AIS和多尺度空间模型的船舶活动时空特征及潜在压力[J]. 大连海事大学学报, 2018,44(3):115-121, 128.
	[ Liu Baijing, Jia Jing, Wu Xiaoqing, et al. Spatial-temporal features and potential pressure of marine vessel activities based on AIS and multi-scales spatial model. Journal of Dalian Maritime University, 2018,44(3):115-121, 128. ]
[21]	刘柏静, 吴晓青, 杜培培, 等. 海域使用活动对海湾生态环境的压力评估: 以莱州湾为例[J]. 海洋学研究, 2018,36(3):76-83.
	[ Liu Baijing, Wu Xiaoqing, Du Peipei, et al. Assessment of potential pressure caused by sea use activities on the eco-environment of bays: A case study in Laizhou Bay, China. Journal of Marine Sciences, 2018,36(3):76-83. ]
[22]	Pedreschi D, Bouch P, Moriarty M, et al. Integrated ecosystem analysis in Irish waters: Providing the context for ecosystem-based fisheries management[J]. Fisheries Research, 2019,209:218-229. doi: 10.1016/j.fishres.2018.09.023
[23]	曹可, 张志峰, 马红伟, 等. 基于海洋功能区划的海域开发利用承载力评价: 以津冀海域为例[J]. 地理科学进展, 2017,36(3):320-326. doi: 10.18306/dlkxjz.2017.03.007
	[ Cao Ke, Zhang Zhifeng, Ma Hongwei, et al. Capacity for resource exploitation based on marine functional zones: A case study in the Tianjin-Hebei coastal area. Progress in Geography, 2017,36(3):320-326. ]
[24]	曾容, 路文海, 杨翼, 等. 渤海生态环境问题与管理对策分析[J]. 海洋开发与管理, 2015,32(5):91-96.
	[ Zeng Rong, Lu Wenhai, Yang Yi, et al. Analysis of ecological environment problems and management countermeasures in Bohai Sea. Ocean Development and Management, 2015,32(5):91-96. ]
[25]	吴培强, 张杰, 马毅, 等. 2010—2015年环渤海海岸线时空变迁监测与分析[J]. 海洋科学进展, 2018,36(1):128-138.
	[ Wu Peiqiang, Zhang Jie, Ma Yi, et al. Coastline dynamics monitoring and analysis around the Bohai Sea using remote sensing images during 2010 and 2015. Advances in Marine Science, 2018,36(1):128-138. ]
[26]	朱金发, 孙文力, 汤华. 船载自识别系统手册 [M]. 北京: 人民交通出版社, 2005.
	[ Zhu Jinfa, Sun Wenli, Tang Hua. Manual of shipboard self identification system. Beijing, China: People's Communications Press, 2005. ]
[27]	Coomber F G, D'Incà M, Rosso M, et al. Description of the vessel traffic within the north Pelagos Sanctuary: Inputs for Marine Spatial Planning and management implications within an existing international Marine Protected Area[J]. Marine Policy, 2016,69:102-113. doi: 10.1016/j.marpol.2016.04.013
[28]	Goerlandt F, Kujala P. Traffic simulation based ship collision probability modeling[J]. Reliability Engineering and System Safety, 2011,96(1):91-107. doi: 10.1016/j.ress.2010.09.003
[29]	Li W F, Mei B, Shi G Y. Automatic recognition of marine traffic flow regions based on kernel density estimation[J]. Journal of Marine Science and Technology, 2018,26(1):84-91.
[30]	王凤武, 郑中义, 吴兆麟. 大风浪船舶安全航行的研究综述[J]. 大连海事大学学报, 2002(4):60-63.
	[ Wang Fengwu, Zheng Zhongyi, Wu Zhaolin. Summarizing study on navigating safely for a ship in the heavy storm waves. Journal of Dalian Maritime University, 2002(4):60-63. ]
[31]	杨润亮. 浅析船舶在大风浪中的航行安全[J]. 中国水运, 2018,18(2):18-19.
	[ Yang Runliang. On the navigation safety of ships in the heavy wind and waves. China Water Transport, 2018,18(2):18-19. ]
[32]	中国海事局. 中国沿海内河水域船舶定线制和报告制 [M]. 北京: 人民交通出版社, 2007.
	[ Maritime Safety Administration of China. The ship's routing and reporting system in China's coastal and inland waters. Beijing, China: People's Communications Press, 2007. ]
[33]	James M, Mendo T, Jones E L. AIS data to inform small scale fisheries management and marine spatial planning[J]. Marine Policy, 2018,91:113-121. doi: 10.1016/j.marpol.2018.02.012

类型	船型分类	小型	中型	大型	巨型
货船	载重吨/万t	<0.5	0.5~2	2~5	>5
货船	占比/%	21.71	40.64	12.74	24.91
油轮	载重吨/万t	<0.6	0.6~3.5	3.5~16	>16
油轮	占比/%	50.46	31.99	14.92	2.63
客船	船长/m	<100	100~185	185~250	>250
客船	占比/%	43.80	53.41	1.19	1.60
渔船	船长/m	<12	12~24	24~60	>60
渔船	占比/%	12.46	40.79	37.27	9.48

船舶类型	低速(0~5 kn)	中速(5~10 kn)	高速(10~15 kn)	较高速(15~20 kn)
货船	13.29	42.56	41.17	2.98
客船	16.86	12.98	48.73	21.44
油轮	15.47	46.29	37.45	0.79
渔船	55.15	41.19	3.59	0.07
全部船舶	29.40	41.36	26.92	2.32

船舶类型	全年	春季(3—5月)		夏季(6—8月)		秋季(9—11月)		冬季(12—2月)
船舶类型	均值/ (艘次/h)	均值/ (艘次/h)	相对变化/%	均值/ (艘次/h)	相对变化/%	均值/ (艘次/h)	相对变化%	均值/ (艘次/h)	相对变化/%
渔船	3153	964	-69.43	1626	-48.43	8517	171.10	1399	-55.62
货船	9980	9412	-5.69	11471	14.94	10303	3.24	8742	-12.40
客船	771	621	-19.46	997	29.31	826	7.13	643	-16.60
油轮	2005	1853	-7.58	2307	15.06	1897	-5.39	1972	-1.65
全部船舶	15909	12851	-19.22	16401	3.09	21543	35.41	12756	-19.80

基于GIS和AIS的渤海海上船舶活动时空特征分析

Spatio-temporal characteristics of ship activities in the Bohai Sea based on GIS and AIS

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 33

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	张华, 刘哲达, 殷小冰. 中国跨省流动人口回流意愿的空间差异及影响因素[J]. 地理科学进展, 2021, 40(1): 73-84.
[2]	张晶飞, 张丽君, 秦耀辰, 王霞, 孙莹莹, 荣培君. 知行分离视角下郑州市居民低碳行为影响因素研究[J]. 地理科学进展, 2020, 39(2): 265-275.
[3]	郭新伟, 余斌, 卓蓉蓉, 曾菊新, 颜梅艳. 江汉平原乡村农户就业变迁及其影响因素研究[J]. 地理科学进展, 2020, 39(12): 2094-2104.
[4]	赵丽元, 韦佳伶. 城市建设对暴雨内涝空间分布的影响研究——以武汉市主城区为例[J]. 地理科学进展, 2020, 39(11): 1898-1908.
[5]	杨奎,张宇,赵小风,文琦,钟太洋. 乡村土地利用结构效率时空特征及影响因素[J]. 地理科学进展, 2019, 38(9): 1393-1402.
[6]	杨小露, 张红, 张春晖. 历史遗址类旅游地的生命周期研究——以美国14家历史遗址公园为例[J]. 地理科学进展, 2019, 38(6): 918-929.
[7]	吴翔华, 陈昕雨, 袁丰. 南京市住房困难人群职住关系及影响因素分析[J]. 地理科学进展, 2019, 38(12): 1890-1902.
[8]	王建顺, 林李月, 朱宇, 艾尼江·杰力力. 西部民族地区流动人口户籍迁移意愿及影响因素——以新疆为例[J]. 地理科学进展, 2018, 37(8): 1140-1149.
[9]	刘扬, 周素红, 张济婷. 城市内部居住迁移对个体健康的影响——以广州市为例[J]. 地理科学进展, 2018, 37(6): 801-810.
[10]	萧凌波. 1736-1911年中国水灾多发区分布及空间迁移特征[J]. 地理科学进展, 2018, 37(4): 495-503.
[11]	朱燕, 侯光良, 兰措卓玛, 高靖易, 庞龙辉. 基于GIS的青藏高原史前交通路线与分区分析[J]. 地理科学进展, 2018, 37(3): 438-449.
[12]	韩增林, 吴爱玲, 彭飞, 孙嘉泽, 夏康. 基于非期望产出和门槛回归模型的环渤海地区生态效率[J]. 地理科学进展, 2018, 37(2): 255-265.
[13]	程敏, 连月娇. 基于改进潜能模型的城市医疗设施空间可达性——以上海市杨浦区为例[J]. 地理科学进展, 2018, 37(2): 266-275.
[14]	贾占华, 谷国锋. 东北地区城市宜居性评价及影响因素分析——基于2007-2014年面板数据的实证研究[J]. 地理科学进展, 2017, 36(7): 832-842.
[15]	周侃, 樊杰, 刘汉初. 环渤海地区水污染物排放的时空格局及其驱动因素[J]. 地理科学进展, 2017, 36(2): 171-181.