Ship Trajectories Pre-processing Based on AIS Data

2018 ◽  
Vol 71 (5) ◽  
pp. 1210-1230 ◽  
Author(s):  
Liangbin Zhao ◽  
Guoyou Shi ◽  
Jiaxuan Yang
Keyword(s):  
Data Mining ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Data ◽  
Density Maps ◽  
Different Types ◽  
Quality Dimensions ◽  
Time Accuracy

Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

scholarly journals Big Data on Vessel Traffic

2019 ◽  
Vol 2019 (275) ◽  
Author(s):  
Serkan Arslanalp ◽  
Marco Marini ◽  
Patrizia Tumbarello
Keyword(s):  
Big Data ◽  
Real Time ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Data ◽  
Data Source ◽  
Statistical Agencies ◽  
New Statistics ◽  
Existing Data

Vessel traffic data based on the Automatic Identification System (AIS) is a big data source for nowcasting trade activity in real time. Using Malta as a benchmark, we develop indicators of trade and maritime activity based on AIS-based port calls. We test the quality of these indicators by comparing them with official statistics on trade and maritime statistics. If the challenges associated with port call data are overcome through appropriate filtering techniques, we show that these emerging “big data” on vessel traffic could allow statistical agencies to complement existing data sources on trade and introduce new statistics that are more timely (real time), offering an innovative way to measure trade activity. That, in turn, could facilitate faster detection of turning points in economic activity. The approach could be extended to create a real-time worldwide indicator of global trade activity.

Mapping Global Shipping Density from AIS Data

2016 ◽  
Vol 70 (1) ◽  
pp. 67-81 ◽  
Author(s):  
Lin Wu ◽  
Yongjun Xu ◽  
Qi Wang ◽  
Fei Wang ◽  
Zhiwei Xu
Keyword(s):  
Collision Avoidance ◽  
Reporting System ◽  
Data Retrieval ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Identity Information ◽  
Density Maps ◽  
Ship Tracks

Mapping global shipping density, including vessel density and traffic density, is important to reveal the distribution of ships and traffic. The Automatic Identification System (AIS) is an automatic reporting system widely installed on ships initially for collision avoidance by reporting their kinematic and identity information continuously. An algorithm was created to account for errors in the data when ship tracks seem to ‘jump’ large distances, an artefact resulting from the use of duplicate identities. The shipping density maps, including the vessel and traffic density maps, as well as AIS receiving frequency maps, were derived based on around 20 billion distinct records during the period from August 2012 to April 2015. Map outputs were created in three different spatial resolutions: 1° latitude by 1° longitude, 10 minutes latitude by 10 minutes longitude, and 1 minute latitude by 1 minute longitude. The results show that it takes only 56 hours to process these records to derive the density maps, 1·7 hours per month on average, including data retrieval, computation and updating of the database.

scholarly journals Evaluation of AIS reception in Arctic regions from space by using a stratospheric balloon flight

Polar Record ◽  
2011 ◽  
Vol 48 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Jesper Abildgaard Larsen ◽  
Jens Dalsgaard Nielsen ◽  
Hans Peter Mortensen ◽  
Ulrik Wilken Rasmussen ◽  
Troels Laursen ◽  
...  
Keyword(s):  
Barents Sea ◽  
The Arctic ◽  
Automatic Identification ◽  
Identification System ◽  
Balloon Flight ◽  
Ship Traffic ◽  
Arctic Regions ◽  
Increased Risk ◽  
Stratospheric Balloon

ABSTRACTDue to the increased melting season in the arctic regions, especially in the seas surrounding Greenland, there has been an increased interest in utilising these waterways, both as an efficient transport route and an attractive leisure destination. However, with heavier traffic comes an increased risk of accidents. Due to the immense size and poor infrastructure of Greenland, it is not feasible to deploy ground based ship monitoring stations throughout the Greenland coastline. Thus the only feasible solution is to perform such surveillance from space. In this paper it is shown how it is possible to receive transmissions from the Automatic Identification System (AIS) from space and the quality of the received AIS signal is analysed. To validate the proposed theory, a field study, utilising a prototype of AAUSAT3, the third satellite from Aalborg University, was performed using a stratospheric balloon flight in the northern part of Sweden and Finland during the autumn of 2009. The analysis finds that, assuming a similar ship distribution as in the Barents Sea, it is feasible to monitor the ship traffic around Greenland from space with a satisfactory result.

Research on Vessel Trajectory Multi-Dimensional Compression Algorithm Based on Douglas-Peucker Theory

2014 ◽  
Vol 694 ◽  
pp. 59-62 ◽  
Author(s):  
Fei Xiang Zhu ◽  
Li Ming Miao ◽  
Wen Liu
Keyword(s):  
Compression Algorithm ◽  
Spatial Distance ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Compression Process ◽  
Maritime Traffic ◽  
Offset Distance ◽  
Improved Algorithm

Currently, maritime safety administrations or shipping company had received a large number of vessel trajectory data from Automatic Identification System (AIS). In order to more efficiently carry out research of maritime traffic flow, ship behavior and maritime investigation, it is important to ensure the quality of the vessel trajectory data under compression condition. In classic Douglas-Peucker vector data compression algorithm, offset spatial distance of each point was the single factor in compression process. In order to overcome the shortcomings of classic Douglas-Peucker, a vessel trajectory multi-dimensional compression improved algorithm is proposed. In improved algorithm, the concept of single trajectory point importance which considers the point offset distance and other vessel handling factors, such as the vessel turning angle, speed variation, is proposed to as the compression index. Compared to classic Douglas-Peucker algorithm, experiment results show that the proposed multi-dimensional vessel trajectory compression improved algorithms can effectively retain characteristics of navigation.

scholarly journals Performance Analysis of a Medium Frequency Offshore Grid for Identification Of Vessels Sailing on High Density Maritime European Routes

2017 ◽  
Vol 24 (4) ◽  
pp. 18-26
Author(s):  
Alfonso López ◽  
Miguel Gutiérrez ◽  
Andrés Ortega ◽  
Cristina Puente ◽  
Alejandro Morales ◽  
...  
Keyword(s):  
Grid Method ◽  
Real Data ◽  
Satellite System ◽  
Simulation Software ◽  
High Density ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Distributed Data ◽  
Medium Frequency

Abstract The paper analyses the performance of an Automatic Vessel Identification System on Medium Frequency (AVISOMEF), which works with the Grid Method (GM) on high density maritime European routes using real data and uniformly distributed data. Compared to other systems, AVISOMEF is a novelty, as it is not a satellite system, nor is it limited by a given coverage distance, in contrast to the Automatic Identification System (AIS), though in exceptional circumstances it leans towards it. To perform the analysis, special simulation software was developed. Moreover, a number of maritime routes along with their traffic density data were selected for the study. For each route, two simulations were performed, the first of which based on the uniform traffic distribution along the route, while the second one made use of real AIS data positioning of vessels sailing on the selected routes. The obtained results for both simulations made the basis for formulating conclusions regarding the capacity of selected routes to support AVISOMEF.

scholarly journals Methods for Processing and Interpretation of AIS Signals Corrupted by Noise and Packet Collisions

2012 ◽  
Vol 49 (3) ◽  
pp. 25-31 ◽  
Author(s):  
J. Poļevskis ◽  
M. Krastiņš ◽  
G. Korāts ◽  
A. Skorodumovs ◽  
J. Trokšs
Keyword(s):  
Software Defined Radio ◽  
Traffic Monitoring ◽  
Automatic Identification ◽  
Identification System ◽  
Coverage Area ◽  
Amplitude Noise ◽  
Packet Collision ◽  
Marine Traffic ◽  
The Common

Methods for Processing and Interpretation of AIS Signals Corrupted by Noise and Packet Collisions The authors deal with the operation of Automatic Identification System (AIS) used in the marine traffic monitoring to broadcast messages containing information about the vessel: id, payload, size, speed, destination etc., meant primarily for avoidance of ship collisions. To extend the radius of AIS operation, it is envisaged to dispose its receivers on satellites. However, in space, due to a large coverage area, interfering factors are especially pronounced - such as packet collision, Doppler's shift and noise impact on AIS message receiving, pre-processing and decoding. To assess the quality of an AIS receiver's operation, a test was carried out in which, varying automatically frequency, amplitude, noise, and other parameters, the data on the ability of the receiver's ability to decode AIS signals are collected. In the work, both hardware- and software-based AIS decoders were tested. As a result, quite satisfactory statistics has been gathered - both on the common and the differing features of such decoders when operating in space. To obtain reliable data on the software-defined radio AIS receivers, further research is envisaged.

Freight Distribution Analysis and Modelling of Inland Waterway Transport along the Yangtze River Economic Belt using Big Data

2022 ◽  
pp. 1-36
Author(s):  
Guihua Deng ◽  
Ming Zhong ◽  
Mo Lei ◽  
John Douglas Hunt ◽  
Wanle Wang ◽  
...  
Keyword(s):  
Yangtze River ◽  
Length Distribution ◽  
Water Levels ◽  
Automatic Identification ◽  
Identification System ◽  
Distribution Analysis ◽  
The Yangtze River ◽  
Distribution Models ◽  
Inland Waterway ◽  
Different Types

The Yangtze River Economic Belt (YREB) serves as the main east-west axis of China to promote economic development and environmental protection along the Yangtze River. This paper analyses the factors that affect the freight distribution of major types of cargo transported through the Yangtze River, using data from the automatic identification system (AIS) and ship visa data. First, a set of freight impedance functions are developed for different types of links of the waterway network, by considering a number of factors such as cargo types, delays at ship locks, water levels and flows at different waterway segments and upstream and downstream shipping speeds. Both the distance- and time-based impedance matrices of different types of cargo are computed, respectively. After that, gravity model (GM) and intervening opportunity model (IOM) are estimated to simulate the distribution of different types of cargo based on the computed impedance matrices. Meanwhile, a trip length distribution (TLD) method is applied to validate the estimated distribution models. The results indicate that GM with a power term outperforms other models, and the time-based models are superior to the distance-based ones for the prediction of freight distributions over large geographies like the YREB. This work offers an in-depth understanding of the freight characteristics of inland waterways and therefore it should be helpful for relevant authorities in formulating their port and inland waterway plans and policies.

scholarly journals How can Automatic Identification System (AIS) data be used for maritime spatial planning?

2018 ◽  
Author(s):  
Matthieu Le Tixerant ◽  
Damien Le Guyader ◽  
Françoise Gourmelon ◽  
Betty Queffelec
Keyword(s):  
Spatial Planning ◽  
Legal Framework ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Legal Questions ◽  
Pertinent Data ◽  
Spatio Temporal ◽  
Maritime Spatial Planning

Although the importance of Maritime Spatial Planning (MSP) as a concept is know acknowledged and the legal framework is in place, the task of applying it remains a delicate one. One of the keys to success is having pertinent data. Knowing how maritime uses unfold in a spatio-temporal context, and what conflicting or synergistic interactions exist between activities, is crucial. However, this information is especially hard to obtain in a marine environment. As a result this information has often been identified as the missing layer in information systems developed by maritime stakeholders. Since 2002, the Automatic Identification System (AIS) has been undergoing a major development. Allowing for real time geo-tracking and identification for equipped vessels, the data that issues from AIS data promises to map and describe certain marine human activities.After recapitulating the main characteristics of AIS and the data it provides, this article proposes to evaluate how AIS is currently used in MSP at a European level, and to concisely present a series of methods and results obtained within the framework of several operational research projects. The objective is to illustrate how the AIS data processing and analysis can produce adequate information for MSP: maritime traffic density, shipping lanes and navigation flows, hierarchical network of maritime routes, alleged fishing zones, spatio-temporal interactions between activities (potential conflicting uses or synergies). The conclusion looks in particular at the legal questions concerning the use of AIS.

scholarly journals Mapping Marine Traffic Density by Using AIS Data: An Application in the Northern Aegean Sea

2018 ◽  
Vol 25 (4) ◽  
pp. 49-58 ◽  
Author(s):  
Burak Kundakçi ◽  
Selçuk Nas
Keyword(s):  
Data Storage ◽  
Aegean Sea ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Cross Sectional ◽  
Marine Traffic ◽  
Desktop Application ◽  
Intersection Algorithm ◽  
Northern Aegean Sea

Abstract Automatic Identification System (AIS) data is used for monitoring the movements of vessels live movements through instant transmission of vessel information while, at the same time, historical AIS data is used for marine traffic analysis by researchers. There are several methods and computer programs developed for the analysis of marine traffic by the use of AIS data. Combining the intersection algorithm proposed by Antonio (1992) and distance calculation method, this study develops a method to analyse vessel distribution on a selected cross sectional line (SCS) in the Northern Aegean Sea. As a complementary to the new methods proposed, a desktop application is developed in C# programming language to visualize the vessel distribution on the SCS line. SQL server is used for AIS data storage and analysis. The study is conducted over 7-day AIS data, specifically 2.382.469 rows and 42.884.442 data in total, belonging to the Northern Aegean Sea marine traffic. As a result, the mapping of the movements of different types of vessels in the Northern Aegean Sea is effectively performed and Frequency-Distance, Draught-Distance, SOG-Distance, SOG-COG distributions on the SCS line are successfully analysed by the new method introduced.

Sign in / Sign up

Export Citation Format

Share Document