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Remote sensing for operational pollution monitoring, source detection and identification
Frascati , Italy14th/15th September 2010
Remote sensing for operational pollution monitoring, source detection and identification
Content
• Technique & methodology for monitoring and detection
• Oil slick detection with SAR
• How man made oil spills look like
• Look-alikes
• The ‘West Cork’ case
• Monitoring Baku off-shore area
• The Adriatic case - I
• The Adriatic case - II
• Lessons learnt
Remote sensing for operational pollution monitoring, source detection and identification
Technique & methodology for monitoring and detection
• Visual
• Air borne– SLAR (Side looking airborne Radar)– LFS (Laser Fluorosensor)– MWR (Microwave radiometry)– IR/UV (Infrared/ultraviolet line scanner)– FLIR (Forward looking infrared)– Camera/video
• Satellite– SAR (Synthetic Aperture Radar)– Optical Sensors
Remote sensing for operational pollution monitoring, source detection and identification
Oil slick detection with SAR
• SAR emits electromagnetic pulses and measures the level of the backscattered signal.
• SAR sensors provide information on the ocean surface roughness. Ocean’s roughness is driven by the wind which creates ripples at the sea surface.
• The presence of a film on the sea surface damps out small waves and reduces the measured backscattered energy which results in darker areas in the SAR imagery.
Low wind: Weak backscattered signal – No contrast between oil slicks and surrounding waters.
Moderate winds favorable for oil detection – Oil slicks appear as dark features in SAR imagery.
High winds: Useful signal lost in the ambient noise – Oil slicks often broken and dispersed into the water column.by O. Trieschmann
Remote sensing for operational pollution monitoring, source detection and identification
How man made oil spills look like
Courtesy of ESA (2007 - 2010)
Remote sensing for operational pollution monitoring, source detection and identification
Look-alikes
• Unfortunately oil slicks are not the only phenomenon which can be detected in similar manner.– fresh water slicks– calm areas (wind slicks)– ship wakes– wave shadows behind land or structures– vegetation or weed beds which calm the
water just above them– glacial flour– biogenic oils– whale and fish sperm
• This is particularly exacerbated in low wind conditions where natural surfactants can easily be confused for spills. Courtesy of ESA (2007 - 2010)
Remote sensing for operational pollution monitoring, source detection and identification
The ‘West Cork’ Case
• Russian convoy consisted of the aircraft carrier Admiral Kuznetsov – 14/02/2009.
• The spill is estimated up to 400 - 500 tons of oil spilled.
ENVISAT/ASAR (14/02/2009 – 10:53 UTC)Photo by Irish Coast Guard
Remote sensing for operational pollution monitoring, source detection and identification
The ‘West Cork’ Case
• Oil spill initially detected ~80 km southeast of Fastnet Rock off the West Cork coast by EMSA CSN.
Photo by Irish Coast Guard
ENVISAT/ASAR (14/02/2009 – 22:51 UTC)
Remote sensing for operational pollution monitoring, source detection and identification
Metocean data, slicks and calculated vessel drift.
The ‘West Cork’ Case
• Polluter Identification and backtracking.
Backtracking results.
Remote sensing for operational pollution monitoring, source detection and identification
Monitoring Baku Off-shore area (2007 – 2010)
Photo by B. Girin
ENVISAT/ASAR (01/08/2010 - 06:42 UTC)
Remote sensing for operational pollution monitoring, source detection and identification
Monitoring Baku Off-shore area (2007 – 2010)
ENVISAT/ASAR (31/07/2010 - 18:31 UTC) MODIS/Aqua (31/07/2010 – 09:45 UTC)
Remote sensing for operational pollution monitoring, source detection and identification
Monitoring Baku Off-shore area (2007 – 2010)
ENVISAT/ASAR (04/08/2010 – 06:47 UTC) MODIS/Terra (04/08/2010 – 07:40 UTC)
Remote sensing for operational pollution monitoring, source detection and identification
The Adriatic Case (I) – ENVISAT/ASAR 21/07/2006 - offshore Ancona (Central Adriatic)
MODIS/Terra (21/07/2006 - 10:25 UTC)ENVISAT/ASAR (21/07/2006 - 09:26 UTC)
Remote sensing for operational pollution monitoring, source detection and identification
The Adriatic Case (I) – ENVISAT/ASAR 21/07/2006 - offshore Ancona (Central Adriatic)
AIS of ‘ASSO DICIANNOVE’ – 21/07/2006.Offshore platform ‘DARIA A-B’ and EQUASIS ship database.
Remote sensing for operational pollution monitoring, source detection and identification
The presented scenarios are instantiated in cooperation with:
Irish Coast Guard
University of Ljubljana, Faculty of Maritime Studies and Transport
Vessel Surveillance and Port security (VESPO) Joint Research Centre (JRC)
The European Maritime Safety Agency (EMSA)
Guardia Costiera Italia
Remote sensing for operational pollution monitoring, source detection and identification
Lessons learnt
• Near Real Time (NRT)
• Multi sensor approach
• Spatial Resolution
• Supplementary data
• Verification
• Feedback
• Training of air crews
Thank you
Dr. Oliver MÜLLENHOFF
BMT ARGOSS
Voorsterweg 28, 8316 PT Marknesse
The Netherlands
Special acknowledgment to:
Marko Perkovic
University of Ljubljana, Faculty of Maritime Studies and Transport
Vessel Surveillance and Port security (VESPO) team
Joint Research Centre (JRC)
