1. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 1 Maritime surveillance in European context Harm Greidanus European Commission – Joint Research Centre

2. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 2 Contents 1.European context of maritime surveillance 2.Maritime surveillance systems 3.Satellite images Application examples 4.Future research

3. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 3 Why maritime surveillance? Problems- Safety Threats- Security Illegal activities- Compliance Search & rescue Maritime traffic control Piracy Terrorism Fisheries control Illegal immigration Smuggling (narcotics) Marine pollution (oil) …

4. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 4 European context Police & Judicial co-oper. AgricultureDefenceR&DTransportFisheriesIndustry European Commission European Union (27 Member States) JRC Research funding in Europe Joint Research Centre: Scientific and technical support for European Union policies (conception, development, implementation and monitoring) Reference centre of science and technology for the EU Serves the common interest of the Member States Independent of special interests (private or national) 2800 Staff, 7 Institutes http://ec.europa.eu/dgs/jrc Energy Aid …

5. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 5 EU policies (maritime) Marine strategy (environment) Common Fisheries Policy Maritime transport – VTMIS directive Directive on ship source pollution Border security: EUROSUR, European Border Surveillance system Border control up to same standards Interoperability and connections between countries Now, focus on southern maritime borders European Security & Defence Policy Operation Atalanta in Gulf of Aden … New: Integrated Maritime Policy http://ec.europa.eu/maritimeaffairs/policy_documents_en.html

6. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 6 EU policies, supporting Space Earth observation from space (GMES – Global Monitoring for Environment and Security) Galileo: Navigation (European GPS) Satellite communications (mostly commercial) Research & Development: FP7 Partial (50 %) funding of R&D projects

7. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 7 Maritime surveillance systems Reporting (cooperative) systems Observation (non-cooperative) systems

8. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 8 Maritime surveillance systems Reporting (cooperative) systems Fishing vessels – VMS Large cargo & passenger vessels – AIS and LRIT Ships in problems – GMDSS, SSAS Reporting to ports and special areas Observation (non-cooperative) systems Camera (optical, infrared) Lidar (laser-radar) Radar Radio Direction Finder Sonar, underwater acoustics

9. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 9 AIS: Automatic Identification System Designed for maritime traffic safety (collision avoidance) Each merchant ship carries a transponder that automatically communicates to all neighbouring ships by VHF radio link Introduced by International Maritime Organisation (IMO) IMO is a UN organisation International Convention for the Safety of Life at Sea (SOLAS) Implemented in national (and EU) legislation ID, position, speed, heading; cargo, draught, origin, destination, … Ships >300 GT, tankers, passenger vessels

10. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 10 AIS receiver on the coast will give local picture Line-of-sight, i.e. out to 30-50 nm (dept. receiver height) Can be even further due to ducting Many countries are installing coastal AIS network International networks collect data from many shores AIS for vessel monitoring

11. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 11 US / NATO’s MSSIS Maritime Safety & Security Information System Global data sharing network of government AIS systems Picture source: Office of Global Maritime Situational Awareness

12. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 12 Satellite AIS – Early results COMDEV / exactEarth

13. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 13 LRIT: Long Range Identification and Tracking Send vessel ID, location to Flag State Every 6 hour (can be changed) Globally, so by satellite communication Cargo vessels > 300 GT, passenger For maritime security; quickly introduced after 9/11 IMO regulation SOLAS From 1 Jan 2008 Confidential Coastal state has access out to 1,000 nm In Europe, centralised by European Maritime Safety Agency (EMSA)

14. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 14 VMS: Vessel Monitoring System Designed for fisheries management and control Automatic position reports from fishing vessels, sent to Flag State’s fisheries inspection authorities (FMC, Fisheries Monitoring Centre) Flag State forwards to Coastal State “Blue box”, GPS receiver + communications unit Global coverage thanks to satellite communications Treated as confidential

15. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 15 VMS details Started 1988 Implementation to national law EU (CFP; since 1996, last 2006): All fishing vessels > 15 m Report every 1-2 hour Vessel ID, position, course, speed Satellite communication can be e.g. INMARSAT-C or ARGOS Implemented in many countries (Russia, US, Canada, Peru, Chile, Australia, New Zealand, …) International leading role of UN FAO

16. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 16 Maritime surveillance systems Reporting (cooperative) systems Fishing vessels – VMS Large cargo & passenger vessels – AIS and LRIT Ships in problems – GMDSS, SSAS Reporting to ports and special areas Observation (non-cooperative) systems Camera (optical, infrared) Lidar (laser-radar) Radar Radio Direction Finder Sonar, underwater acoustics

17. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 17 Satellite remote sensing Basis for VDS (Vessel Detection System) Images from satellite Will show vessels on the sea One snapshot as the satellite passes; no continuous monitoring Typically, 1 image every few days Polar orbit (Equatorial orbit) Polar orbit 400-800 km 36,000 km

18. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 18 Optical satellite images High resolution (<1-10 m) Small area (10-60 km) Daytime, clear skies  Use for recognition Radar satellite images Low resolution (8-50 m) Wide area (up to 400 km) Indept. clouds, night  Use for detection Cargo ships in Istanbul IKONOS satellite Line of fishing vessels in NE Atlantic RADARSAT satellite Radar and optical images Preferred

19. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 19 SPOT-5 10 m color SPOT footprint, 60 x 60 km Optical satellite images SPOT-5 10 m multispectral

20. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 20 SPOT-5 10 m color Optical satellite images SPOT-5 2.5 m b/w

21. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 21 Optical satellite images QuickBird Tuna cages Sub-meter resolution, ~15 km swath EROS 1.8 m b/w

22. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 22 Synthetic Aperture Radar (SAR) Radar, suitable for use on satellite Wide area, low resolution Narrow area, high resolution High resolution (<10 m) only when sea is calm

23. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 23 Satellite radar image – Wide 50-150 m resolution 300-400 km swath only to show relative size, not actual zoom  ENVISAT-ASAR © ESA

24. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 24 Satellite radar image – Standard 25 m resolution 100 km swath ENVISAT-ASAR © ESA RADARSAT © CSA/MDA

25. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 25 Satellite radar image – High resolution 10 m resolution 50 km swath RADARSAT © CSA/MDA

26. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 26 26 m fishing boat 33 m fishing boat 20 m fishing boat Ships in 100x100 km SAR images (25 m resolution)

27. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 27 TerraSAR-X Stripmap 3 m resolution Caribbean, June 2008 160 m TerraSAR-X Scansar 15 m resolution Caribbean, June 2008 230 m Merchant Vessel EADS Astrium, JRC, EUSC, SPOT Image, Nev@ntropic

28. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 28 Radarsat-2 UltraFine HH Jan 2009 TerraSAR-X Spotlight 1.5 m resolution Caribbean, June 2008 18 m 5-12 m Fishing vessel Sailing boat SAR – High resolution in narrow swaths TerraSAR-X © Infoterra 2008 RADARSAT © CSA/MDA 2009

29. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 29 Sea surface backscatter Radar backscatter Surface roughness Wind Backscatter when surface roughness has wavelength of the same order as radar wavelength (5 cm) Backscatter proportional to roughness amplitude “Bragg backscattering”

30. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 30 Radarsat-1 ScanSAR Narrow A 17 Sept 2003 16:13 UTC Oil spills and slicks Natural slicks ERS-1 Envisat Wide Swath VV 16 Sept 2003 20:03 UTC

31. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 31 Tidal area Ocean waves Wind front Internal waves Wind effect Ocean features

32. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 32 Sea bottom topography North Sea Rhine outflow ERS image River outflow fronts Heavy rain cells Baltic Sea RADARSAT Std Ocean features

33. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 33 Direct reflections from objects Reflections from sea surface Indirect effects Indirect Direct Sea Backscatter by vessels

34. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 34 Current 3D Surface current Surface roughness contrasts Radar image contrasts Surface roughness Wind Image from C.V. Swanson Types of wakes Kelvin Turbulent Narrow-V Internal wave Ship wakes Wave and current pattern set up by passing ship

35. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 35 Ship wakes (II) Optical: SPOT Radar: ERS-2 Corsica

36. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 36 9785 18 43 Ship traffic survey

37. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 37 Traffic routes

38. Pompei, April 2009 Use of Satellite AIS

39. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 39 Tracking the “Jolly Verde”: Genova – Horn of Africa – South Africa and back Coastal AIS, Satellite AIS, Ship-logged AIS, Satellite SAR 12 Aug 2009, 02:53 UT MSSIS S 07° 04’ 20”, E 39° 42’ 53” D’Appolonia, JRC, EADS Astrium, Telespazio, KSAT, EUSC Radarsat-2 SCN © MDA/CSA 2009

40. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 40 Ship detection Correlate with VMS, AIS and surveillance reports Total: 30 min Suspect positions to authorities Vessel Detection System (VDS) AIS Acquisition Downlink Processing FTP to JRC VMS

41. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 41 Example: 25 July 2008 57 VDS (satellite targets) Strong signatures Others Correlations with VMS & AIS data AIS data 2 cargo vessels all correlated VMS data 9 Fishing vessels out of port 8 correlated 1 uncorrelated 20 additional VDS reported to surveillance means as “suspected targets” possible illegal fishing (to check) Two Radarsat Standard images Mediterranean Visualise results in Google Earth Used as pilot in Mediterranean tuna fishing control campaigns to direct Member State patrol vessels

42. 42 Sat image, AIS shipping, HF currents and Wind Stress on top Navigational chart PISCES 2 - Transas TechnologyINGV – NASCUM project on HF currents ESA - ENVISAT/MERIS INTEGRATION ISRSE-33 – Stresa, 07.05.2009

43. 43 Backtracking the polluter - animation ISRSE-33 – Stresa, 07.05.2009 M. Perkovic et al., ISRSE 33, 4-8 May 2009

44. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 44 Way ahead – research needed Improvement of sensors Detecting small boats over wide areas More flexible / cheaper platforms Unmanned Aerial Vehicles (UAV), balloons, … Better processing Automatic flagging of anomalies Further integration of data From different sensors By different users

45. University of Ljubljana, Faculty of Maritime Studies and Transport, 28 Oct 2009 45 Harm.Greidanus @ jrc.ec.europa.eu EC Joint Research Centre TP 670 21020 Ispra (VA), Italy T +39-0332-78 9739 http://ipsc.jrc.ec.europa.eu http://maritimeaffairs.jrc.ec.europa.eu The end