Shipping Routes Project
Scott Phan
An Nguyen
Presentation
27, June 2011
studyabroad.iit.demokritos.gr
Institute of Informatics and Telecommunications – NCSR “Demokritos”
Shipping in the Aegean Sea
 Mediterranean Sea supports between 4-18% of the worlds
species
 Aegean Sea is an area of the Mediterranean which carries
high biological importance, due to the relatively low coastal
development.
 However, the preservation of this ecosystem is being left
largely to chance, with few protection measures in place. If
damage to the area increases or a major event the results
could be severe.
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Shipping in the Aegean Sea
 Hundreds of cargo, tanker and passenger ships pass through
the Aegean Sea every day. The potential impacts of
shipping, commercial and recreational, are vast.
 Ships can affect marine biota in the following ways:
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Underwater noise created by ships
Anchoring
Grounding
Direct collisions
Carrying invasive species
Operational oil discharges
Accidental oil discharges
Thermal Discharges
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Project Motivation
 The Aegean Sea lacks efficient mechanisms to manage,
monitor and regulate ship traffic conditions.
 To decrease the chance of ecological disturbance events,
strict shipping lanes must be established and enforced.
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Project Motivation
 Over the last few months, the marine and GIS teams from
Archipelagos have been working on a major shipping project.
 From November 12, 2009 to April 29, 2010, data on all of
the tankers and cargos that travelled between Samos,
Ikaria, Mykonos, Andros, and Nisos Evia were recorded.

The data was received from www.marinetraffic.com and
www.mariweb.gr, which track and record data from shipping
vessels.
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Project Motivation
Accumulated Ship
Trajectories in the Aegean
Article:
“Update on Shipping Data
collection at Archipelagos”
-Chris Fletcher
Link
http://workjournal.archipelago.gr/?p=1348
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Project Goals
Database
Design/Implementations
Import/Decode AIS data
GUI Design/Data
Visualization
Data Mining / Risk
Management
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Project Goals: Details
1. Create a Graphical User Interface (GUI) [done]
2. Place ship markers at arbitrary pixel locations on the map [done]
3. Parse the AIS database and plot each ship at a given time interval on the
map [done]
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Project Goals: Details
4. Create a function to assign a scalar “risk value” for each ship given
certain database attributes for each ship (cargo, size, proximity to
coast and other ships, flag, etc) [In Progress]
5. Create a visual identifier to show the risk of each ship (change
color, display numeric label, etc) [done]
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Project Goals
7. Create a function to assess the risk of a particular map pixel
location based on the number and proximity of ships within a given
radius and proximity to land [In Progress]
8. Create a map view which shows risky areas in red and less risky
areas in green/blue. This “risk density map [In Progress]
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Approach: Area of Interest
Spatial Bounds
Lat [35, 39]
Lon [21, 29]
Aegean Sea
Ignore all data that
falls outside the
boundaries
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Approach: About the Input
 Huge data collections
 Good facilities to collect real time data
 Accurate information to predict the trend of routes and risk
management
 Used dataset provided by International Maritime Information
Systems (IMIS)
– Covers 2 days worth of AIS messages
 Challenges with the IMIS dataset:
– Raw data - not decoded
– Not well managed
 Redundant data (3x redundant)
– Database not as supportive for GIS development
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Approach: About the Input
 Automatic Identification System (AIS)
– is an automated tracking system used on ships and by Vessel Traffic
Services (VTS) for identifying and locating vessels by electronically
exchanging data with other nearby ships and VTS stations.
– AIS information supplements marine radar, which continues to be the
primary method of collision avoidance for water transport.
 Types of Info. Encapsulated within the Messages
– Static [MMSI number, IMO number, callsign, ship name and
type, dimension]
– Dynamic [position, time, speed, heading, course over ground,
rate of turn, navigational status]
– Trajectory-based [destination, estimated time of arrival,
draught]
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Approach: About the Input
 Encoded Spatial Data within the Database
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Approach: About the Input
 Decoding the Encoded Spatial Data
Input :
0101000020E6100000000000604A653840000000E0FBB14240
Decoding
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Approach: Software Architecture
Database
NASA 3D maps API
IMIS Database
Control
SQL Query
Raw Data
3D maps
Controller
Graphic User Interface
GUI
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Approach: Graphical User Interface
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Approach: Data Flow Architecture (Part I)
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Approach: Data Flow Architecture
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Approach: Output - Visualization
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Approach: Output - Visualization
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One more thing
27/06/2011
How we get data?
MySQL dump files
Extracted AIS Data
PostgreSQL/PostGIS
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How long does it take?
3hours/file
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SQL Importing Tool
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Demo
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Future Work
1. Prepare paper for publishing
2. Implement proximity function to find nearest
land from a given point in the sea
3. Design and implement the data mining API and UI
4. Research shipping risk assessment methods
5. Implement density plotting with respect to risk
assessment of a spatial area
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Acknowledgements


Archipelagos - Institute of Marine Conservation
“KNOWLEDGE DISCOVERY FROM MARITIME MOVING OBJECTS APPLICATION TO AEGEAN SEA” – Cyril Ray, Naval Academy Research Lab,
December 2010

NCSR Demokritos

University of The Aegean

International Maritime Information Systems (IMIS)

CSE Dept. @ University of Texas at Arlington
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Questions?
27/06/2011