WP 2 – Tracking shipping traffic Dr. Alan Deidun

1. WP 2 – Tracking shipping traffic Dr. Alan Deidun

2. Population distribution by Ship Type Top 40 Ship Types extracted from: AIS dataset (From: 2013-02-12 To: 2013-07-16) and Total 90 ship categories circa in 8839 unique records

3. Population distribution by Ship Type – Pie Chart Top 40 Ship Types extracted from: AIS dataset (From: 2013-02-12 To: 2013-07-16) and Total 90 ship categories circa in 8839 unique records

4. Length Statistics for Top 40 Ship Types (m) Extracted from: AIS dataset (From: 2013-02-12 To: 2013-07-16) and Total 90 ship categories circa in 8839 unique records of which 6700 report Ship Length

5. Top 20 Ship Types having the highest Maximum Length (m) Extracted from: AIS dataset (From: 2013-02-12 To: 2013-07-16) ,Total 90 ship categories circa in 8839 unique records

6. Maximum, Minimum, Average Length per Ship type Top 30 Ship Types having the highest Average Length (m)Extracted from: AIS dataset (2013-02-12-2013-07-16) ,Total 90 ship categories circa in 8839 unique records

7. Histogram for Ship Length AIS data (From: 2013-02-12 To: 2013-07-16)

8. Top 50 Destinations Extracted from: AIS dataset (From: 2013-02-12 To: 2013-07-16) and Total 406186 unique records

9. Spatial Tool Development

10. 1 km boundary line

11. 5 km boundary line

12. 12 km boundary line

14. Histogram for Ship Speed to understand Ship Speed Frequency between 0 and 2 knotsAIS data (From: 2013-02-12 To: 2013-07-16),406186 unique records

15. Navigation Status Frequencies - for ships within the 12km boundary

16. Prototype showing the 1, 5 and 12 km boundaries as overlays

17. User Controls to define Ship Positions and Date Ranges displayed

18. User Controls to define Ship Status (Anchored/Underway) displayed

19. User Controls to define Ship Type Categories displayed

20. Ship Position Window Collective Information Window Adding the Information statistics, Ship Position Window

21. User Selection validation

22. Without grouping criteria

23. With grouping criteria

24. With grouping criteria and ship speed <=0.2 knots considered as anchored

25. Prototype: showing 10,000 ship positions Artefact 1

26. Artefact 1 Artefact 1 at higher zoom Artefact 1

27. Experimenting with clustering

28. Clusters break up into smaller clusters at higher zoom levels

29. Clusters break up into smaller clusters and individual positions at higher zoom levels

30. Aggressive clustering approach is enabled for groups as small as 2 points or more

31. Clustering is enabled for groups composed of 20 points or more in the 60 pixel range

32. Aggressive clustering approach is enabled for groups as small as 2 points or more as seen at a higher zoom level

33. Clustering is enabled for groups that have are made of 20 points or more AS SEENat a higher zoom level

34. Dataset Status - BioDiValue Trackers

35. High Level Process – From AIS Antenna to BioDiValue Tracker

36. High level requirements Collate and update data as per established CSV format and guidelines Upload and import CSV file directly to MySQL database feeding BioDiValue Tracker to refresh historical data available through web interface Benefits Most of the infrastructure is already in place Limited know how transfer is required to update the system from time to lime Limitations Requires human intervention every time to manually update BioDiValue Tracker Dataset available through BioDiValue Tracker will not be close to real time as in Scenario 2 Dataset quality is expected to vary as sources may not be automated as in scenario 2. SeperateBioDiValue Tracker for every location in Sicily No pre-processing of dataset to allow user to select vessel positions according to defined distance from coastline from BioDiValue Tracker May give rise to inconsistencies when assimilating data sources for different locations into one BioDiWare software Scenario 1 - manual upload of historical datasets into BioDiValue Trackers specific to location

37. High level requirements • Setup infrastructure as in high level process described in previous slides using software and practices that are already in function for BioDiValue Tracker – Malta • Knowledge transfer from BioDiValue Tracker – Malta to implement in Sicily Benefits • Automated process from data capture through AIS Antenna to BioDiValue Tracker • Better opportunity provide consistent and timely datasets to BioDiValue Trackers and input to BioDiWare software. Datasets available through BioDiValue Tracker are expected to be as close to real time as can be. Dataset quality expected to be consistent throughout as AIS data feed is subject to standards. • Less prone to human errors related to manually handling updates every time • Depending on AIS implementation it may be possible to capture AIS data from several nearby locations in one BioDiValue Tracker • Pre-processing of dataset allows user to select vessel positions according to defined distance from coastline from BioDiValue Tracker Limitations • Require more infrastructure when and if more than one AIS antenna feed is to be combined (minimum 1 in Sicily depending on topology and 1 in Malta) in one BioDiValue Tracker. This complication can be avoided by developing a BioDiValue Tracker for every antenna. Combined feeds from multiple AIS Antenna’s that overlap in range require changes to the preprocessing before pushing the data onto the BioDiValue Tracker. • Significant resources need to be allocated for knowledge transfer to happen and support period to ensure a smooth implementation Scenario 2 - near real time update of Biodivalue Trackers through AIS antenna feed