scholarly journals Study of narrow waterways congestion based on automatic identification system (AIS) data: a case study of Houston Ship Channel

2021 ◽  
Author(s):  
Masood Jafari Kang ◽  
Sepideh Zohoori ◽  
Maryam Hamidi ◽  
Xing Wu
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Houston Ship Channel

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.

scholarly journals Recreational vessels without Automatic Identification System (AIS) dominate anthropogenic noise contributions to a shallow water soundscape

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Line Hermannsen ◽  
Lonnie Mikkelsen ◽  
Jakob Tougaard ◽  
Kristian Beedholm ◽  
Mark Johnson ◽  
...  
Keyword(s):  
Noise Pollution ◽  
Marine Species ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
High Speeds ◽  
Recreational Vessels ◽  
Vessel Noise ◽  
Noise Models

Abstract Recreational boating is an increasing activity in coastal areas and its spatiotemporal overlap with key habitats of marine species pose a risk for negative noise impacts. Yet, recreational vessels are currently unaccounted for in vessel noise models using Automatic Identification System (AIS) data. Here we conduct a case study investigating noise contributions from vessels with and without AIS (non-AIS) in a shallow coastal area within the Inner Danish waters. By tracking vessels with theodolite and AIS, while recording ambient noise levels, we find that non-AIS vessels have a higher occurrence (83%) than AIS vessels, and that motorised recreational vessels can elevate third-octave band noise centred at 0.125, 2 and 16 kHz by 47–51 dB. Accordingly, these vessels dominated the soundscape in the study site due to their high numbers, high speeds and proximity to the coast. Furthermore, recreational vessels caused 49–85% of noise events potentially eliciting behavioural responses in harbour porpoises (AIS vessels caused 5–24%). We therefore conclude that AIS data would poorly predict vessel noise pollution and its impacts in this and other similar marine environments. We suggest to improve vessel noise models and impact assessments by requiring that faster and more powerful recreational vessels carry AIS-transmitters.

scholarly journals (AUTOMATIC IDENTIFICATION SYSTEM (AIS) SATELIT DATA CORRECTION USING INTERPOLATION AND EXTRAPOLATION METHODE, (Case Study : LAPAN-A2 and LAPAN-A3 Satellite))

2019 ◽  
Vol 16 (2) ◽  
pp. 159
Author(s):  
Abdul Karim
Keyword(s):  
Big Data ◽  
Technology Use ◽  
Multiple Access ◽  
Automatic Identification ◽  
Identification System ◽  
Extrapolation Methods ◽  
Automatic Identification System ◽  
Valid Data ◽  
Time Division

Nasional Institute Aerounautics and Space (LAPAN) has two satellites (LAPAN-A2 and LAPAN-A3) that are carry Automatic Identification System (AIS) sensors. It can be use for monitoring Indonesian maritime. The altitude of the satellite about 642 Km and 500 km so it has a wide area covered and receive big data. The problem is the AIS technology use the Time Division Multiple Access (TDMA) system that has limitations in handling big data so that some data received can be damaged due to collision. Therefore, in this research has been done the analysis and correction data using interpolation and extrapolation methods. The results  is improvements of valid data about 22,6 % for LAPAN-A2 satellite and 20,8 % for LAPAN-A3 satellite.

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