scholarly journals Massive Automatic Identification System Sensor Trajectory Data-Based Multi-Layer Linkage Network Dynamics of Maritime Transport along 21st-Century Maritime Silk Road

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4197 ◽  
Author(s):  
Hongchu Yu ◽  
Zhixiang Fang ◽  
Feng Lu ◽  
Alan T. Murray ◽  
Zhiyuan Zhao ◽  
...  
Keyword(s):  
Traffic Flow ◽  
21St Century ◽  
Network Structure ◽  
Network Dynamics ◽  
Silk Road ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Automatic Identification System ◽  
Maritime Silk Road

Automatic Identification System (AIS) data could support ship movement analysis, and maritime network construction and dynamic analysis. This study examines the global maritime network dynamics from multi-layers (bulk, container, and tanker) and multidimensional (e.g., point, link, and network) structure perspectives. A spatial-temporal framework is introduced to construct and analyze the global maritime transportation network dynamics by means of big trajectory data. Transport capacity and stability are exploited to infer spatial-temporal dynamics of system nodes and links. Maritime network structure changes and traffic flow dynamics grouping are then possible to extract. This enables the global maritime network between 2013 and 2016 to be investigated, and the differences between the countries along the 21st-century Maritime Silk Road and other countries, as well as the differences between before and after included by 21st-century Maritime Silk Road to be revealed. Study results indicate that certain countries, such as China, Singapore, Republic of Korea, Australia, and United Arab Emirates, build new corresponding shipping relationships with some ports of countries along the Silk Road and these new linkages carry significant traffic flow. The shipping dynamics exhibit interesting geographical and spatial variations. This study is meaningful to policy formulation, such as cooperation and reorientation among international ports, evaluating the adaptability of a changing traffic flow and navigation environment, and integration of the maritime economy and transportation systems.

scholarly journals Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 40
Author(s):  
Naixia Mou ◽  
Haonan Ren ◽  
Yunhao Zheng ◽  
Jinhai Chen ◽  
Jiqiang Niu ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Network Flow ◽  
Road Traffic ◽  
Flow Analysis ◽  
Silk Road ◽  
Identification System ◽  
Traffic Network ◽  
Trajectory Data ◽  
Maritime Traffic ◽  
Maritime Silk Road

Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk Road traffic network. In this study, we used a complex network theory along with social network analysis and network flow analysis to analyze the spatial distribution characteristics of maritime traffic flow of the Maritime Silk Road; further, we empirically demonstrate the traffic inequality in the route. On this basis, we explore the role of the country in the maritime traffic system and the resulting traffic relations. There are three main results of this study. (1) The inequality in the maritime traffic of the Maritime Silk Road has led to obvious regional differences. Europe, west Asia, northeast Asia, and southeast Asia are the dominant regions of the Maritime Silk Road. (2) Different countries play different maritime traffic roles. Italy, Singapore, and China are the core countries in the maritime traffic network of the Maritime Silk Road; Greece, Turkey, Cyprus, Lebanon, and Israel have built a structure of maritime traffic flow in the eastern Mediterranean Sea, and Saudi Arabia serves as a bridge for maritime trade between Asia and Europe. (3) The maritime traffic relations show the characteristics of regionalization; countries in west Asia and the European Mediterranean region are clearly polarized, and competition–synergy relations have become the main form of maritime traffic relations among the countries in the dominant regions. Our results can provide a scientific reference for the coordinated development of regional shipping, improvement of maritime competition, cooperation strategies for countries, and adjustments in the organizational structure of ports along the Maritime Silk Road.

scholarly journals Oil Flow Analysis in the Maritime Silk Road Region Using AIS Data

2020 ◽  
Vol 9 (4) ◽  
pp. 265 ◽  
Author(s):  
Yijia Xiao ◽  
Yanming Chen ◽  
Xiaoqiang Liu ◽  
Zhaojin Yan ◽  
Liang Cheng ◽  
...  
Keyword(s):  
Flow Analysis ◽  
Silk Road ◽  
Energy Information Administration ◽  
Automatic Identification ◽  
Identification System ◽  
General Direction ◽  
Maritime Silk Road ◽  
Oil Flow ◽  
Straits Of Malacca ◽  
The U.S

Monitoring maritime oil flow is important for the security and stability of energy transportation, especially since the “21st Century Maritime Silk Road” (MSR) concept was proposed. The U.S. Energy Information Administration (EIA) provides public annual oil flow data of maritime oil chokepoints, which do not reflect subtle changes. Therefore, we used the automatic identification system (AIS) data from 2014 to 2016 and applied the proposed technical framework to four chokepoints (the straits of Malacca, Hormuz, Bab el-Mandeb, and the Cape of Good Hope) within the MSR region. The deviations and the statistical values of the annual oil flow from the results estimated by the AIS data and the EIA data, as well as the general direction of the oil flow, demonstrate the reliability of the proposed framework. Further, the monthly and seasonal cycles of the oil flows through the four chokepoints differ significantly in terms of the value and trend but generally show an upward trend. Besides, the first trough of the oil flow through the straits of Hormuz and Malacca corresponds with the military activities of the U.S. in 2014, while the second is owing to the outbreak of the Middle East Respiratory Syndrome in 2015.

scholarly journals Analyzing Interactions between Japanese Ports and the Maritime Silk Road Based on Complex Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Zhi-Hua Hu ◽  
Chan-Juan Liu ◽  
Paul Tae-Woo Lee
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Silk Road ◽  
Automatic Identification ◽  
Identification System ◽  
Belt And Road Initiative ◽  
Connectivity Analysis ◽  
Maritime Silk Road ◽  
Maritime Networks ◽  
Belt And Road

This article considers how the Japanese ports interact with the ports of China and along the 21st century Maritime Silk Road (MSR) while they are embedded in the global port network, especially in the context of China’s Belt and Road Initiative. At a port level, it primarily uses connectivity analysis to analyze the port relations and significances in the maritime network. In contrast, at the network level, it applies the methods from network sciences to analyze the significances of these maritime networks and the interactions among the maritime networks of Japan, China, and MSR. This article extracts a large-scale maritime network from ports and vessels’ profiles and data of vessels’ Automatic Identification System (AIS). It then examines the relations among the networks (including Japan, China, MSR, and global ports) after defining the maritime networks, network generation schemes, and port network analysis tools. Based on the analysis results and findings, this study draws some implications for regional ports and shipping development and the global supply network.

scholarly journals Automatic Identification System based Fishing Trajectory Data Preprocessing Method using Map Reduce

2019 ◽  
Vol 8 (2S6) ◽  
pp. 352-356
Keyword(s):  
Radio Channel ◽  
Automatic Identification ◽  
Identification System ◽  
Time Interval ◽  
Fishing Gear ◽  
Trajectory Data ◽  
Test Dataset ◽  
Automatic Identification System ◽  
Proposed Model ◽  
Types Of Information

Many countries use vessel monitoring system (VMS) data to monitor their fishery activities. However, VMS data is limited in terms of distinguishing operations involving illegal fishing gear. Recently introduced automatic identification system (AIS) data is advantageous for tracking fishing ship behaviors.AIS data include various types of information about a ship, such as its state of navigation and its broadcast rate on the radio channel. We interpolate AIS trajectory data with a regular time interval and extract the ship velocity and course change data for fishing ship gear classification. To simplify and condense the data, the course change index (CCI) and ship speed index (SSI) are applied to the ship velocity and course data. The proposed mapper combines CCIs and SSIs into key words, while the proposed reducer collects fishing ship gear type values that are of the same key.By using the proposed key-value dataset from the MapReduce procedure, we can classify fishing gear type. We evaluated the performance of the proposed model by using a test dataset. The results showed that the proposed model achieved 76.2% accuracy in the classification of fishing ship trajectories against the test dataset.

Automatic Identification System Receiver for Small Fishing Vessels

2020 ◽  
Author(s):  
Febus Reidj G. Cruz ◽  
Jeremiah A. Ordiales ◽  
Malvin Angelo C. Reyes ◽  
Pinky T. Salvanera
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Fishing Vessels

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

Sign in / Sign up

Export Citation Format

Share Document