Fig 4 - available via license: Creative Commons Attribution 3.0 Unported
Content may be subject to copyright.
The shipping density map in August & September, 2017 To further verify the effectiveness of the proposed method and experimental results, a world shipping map generalized by the Central Intelligence Agency (CIA) of America is selected and shown in Figure 5 [15], and the level of routes on the map indicate the significance of route, not fully volume the maritime traffic.
Source publication
Due to the current shortage of maritime shipping density assessment methods, a method of shipping density assessment based on trajectory big data is proposed. Firstly, in order to obtain the trajectories following the actual situation, the AIS data is pre-processed. Secondly, as the minimum calculation unit, the grid is constructed, and the shippin...
Context in source publication
Context 1
... on the AIS data that had been pre-processed, grids at resolution 3 minute by 3 minute had been constructed. The basic parameters of the PC used for the experiments are shown in Table 3, and the visualization of shipping density map is as shown in Figure 4. [15], and the level of routes on the map indicate the significance of route, not fully volume the maritime traffic. ...
Similar publications
The Hadoop platform forms a complete large-scale ecological distribution system, including HDFS, MapReduce, HBase and other subsystems. This paper analyzes the parallel processing of Hadoop platform and applies it in the field of data mining algorithms. In order to obtain better algorithm efficiency, a K-Modes clustering algorithm based on big data...
This article starts from the actual situation of graduates of engineering surveying schools that are highly integrated with school-enterprise, in order to continuously improve the quality of teaching, promote the construction of engineering measurement technology, meet the needs of employers and adapt to the trend of social development, and work fo...
Citations
... The first is to make the data appear at the same frequency and the second is to unify the timestamp to facilitate subsequent data calculations. Meanwhile, the period and quantity of AIS data to be processed are large, which should be processed more simply, and the interpolation interval is finally set at 5s, considering the sending interval of AIS data (12s for 0-14 knots, 6s for 14-23 knots, and even shorter time interval when changing course) (Dai et al., 2019) and the research demand. Taking these aspects together, this study conducted a linear interpolation on the AIS data from March 2022 at 5-second intervals (Zhang et al., 2017). ...
... The statistical information includes the number of AIS messages sent, the interval between AIS messages, the number of ships passing through the grid and how long the ships stay in the grid. Dai et al. (2019) proposed a grid-based ship density assessment method, which uses the frequency of ships in the grid as an index to evaluate the ship density in the grid. Liu et al. (2019) proposed a ship density model based on the radial distribution function in molecular dynamics, which identifies the density based on the relative distance between ships. ...
To explore the regularity of ship density and ensure the safety of maritime traffic, a ship density model based on ship scale conversion and grid is established by considering the impact of ship size on traffic safety. A non-parametric kernel density estimation (KDE) method is used to obtain the probability density function of the ship density by selecting the appropriate kernel function and determining the optimal bandwidth. To process and store Automatic Identification System (AIS) data efficiently, a grid-based storage method of AIS data is proposed in this paper, and the relationship between grid width and sampling interval is established. The experiments result proves that the grid-based AIS data storage method saves 64% of storage space compared with the original AIS data. The ship density model based on ship scale conversion can reflect the impact of ship size on the maritime traffic. The distribution regularity of ship density can be obtained through the probability density curve of ship density and statistical characteristics. The research results show that the proposed method can provide theoretical support for the safety supervision of the maritime authority. It can also be recommended for the evaluation of VTS centers in vessel traffic management.
Coupled with digital-enabled Industry 4.0 development, shipping operators increasingly leverage popular digital technologies to innovate green shipping practices. This study provides insights into the concept, adoption, and challenges of digital green shipping innovation (DGSI) to advance knowledge in the field. Such innovation elevates green shipping for environmentally friendly cargo handling and movement by digital technology applications. Against this backdrop, this study reviews literature involving DGSI and identifies four categories of practices. We develop propositions concerning its antecedents and outcomes to understand its adoption. The challenges and opportunities for adopting DGSI are also identified with managerial guidance to plan green innovation in the shipping industry. This research enriches the knowledge of green shipping in the digital-enabled era with insights and guideposts for managers and policymakers to understand the value of digital technologies for greener shipping operations.
For developing national maritime traffic routes through the coastal waters of Korea, the customary maritime traffic flow must be accurately identified and quantitatively evaluated. In this study, the occupancy time of ships in cells was calculated through a density analysis based on automatic identification system data. The density map was statistically created by logarithmically transforming the density values and adopting standard deviation-based stretch visualization to increase the normality of the distribution. Many types of traffic routes such as open-sea, coastal, inland, and coastal access routes were successfully identified; moreover, the stretch color ramp ratio was reduced to identify routes having relatively high density. Adopting a single standard deviation and demonstrating the top 25% of color ramps, the analysis afforded the main routes through which customary traffic flows. This novel density analysis method and statistical visualization method is expected to be used for developing national maritime traffic routes and should ultimately contribute to maritime safety. Moreover, it provides a scientific means and simulator for determining the navigation area and analyzing conflicts with other activities in marine spatial planning.
