tracking surface oil - oil spill response limited · 2017-02-24 · oil emulsion detection...
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Tracking Surface Oil
Ian R. MacDonald Florida State University
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Overview
• The Gulf of Mexico has abundant natural seeps.
• A flow-chart of remote sensing applications
• Oil spill methods—where does remote sensing fit in?
• Lessons from the Gulf—DWH and beyond
• The problem of thickness
• At the cutting edge—bring on the drones
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Floating oil is a tracer for seeps, visible in satellite SAR
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MacDonald et al. 2015 doi:10.1002/2015JC011062 Fig. 1
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MacDonald et al. 2015 doi:10.1002/2015JC011062 Fig. 2
NW 69%
SW 24%
NE 7%
SE 0%
Oil Cover
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White et al. 2016 Oceanography 29 76-87
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Cycle of Remote Sensing Applications Applied to a Unique Spill
Detection
• Genuine spill?
• Where?
• Ongoing?
Evaluation
• Quantity?
• Rate?
• Actionable?
Tactical Response
• Deploy assets?
• Movement?
• Containment?
Injury & Damage Assessment
• Distribution
• Resource intersection
• Impact
• Lessons learned
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1504 m
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Priority Oil—Based on Ensemble Sensor Suite
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Characterize Surface Oil Distributions Using Synthetic Aperture Radar
Satellite SAR image processing was performed using TCNNA algorithm (Garcia-Pineda, Zimmer et al. 2009, Garcia-Pineda, MacDonald et al. 2010)
TCNNA is an FSU developed algorithm which employs satellite and meteorological variables, and textural analysis to extract oil features from RADAR images.
Each SAR pixel is classified as feature or non-feature and to reproduce, pixel by pixel, classifications an expert human analyst would make evaluating whether a given group of pixels belongs to a feature.
For WAMOST, additional routines were developed to output multiple values corresponding to apparent oil thickness categories.
MacDonald et al. (in review) Remote Sensing Assessment of Surface Oil Transport and Fate during Spills in the Gulf of Mexico, BOEM Report
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Oil Emulsion Detection Algorithm
– A publication for WAMOST (Garcia-Pineda, MacDonald et al. 2013) describes the development of the Oil Emulsion Detection Algorithm.
– The Deepwater Horizon spill generated large areas of rainbow sheen and smaller regions of emulsified oil.
– Comparison of aerial photos and surface samples with SAR images found that emulsion produced a radar signature with intermediated intensity between unoiled water and floating sheen.
– This signature was used to segment areas of oil emulsion in 60 SAR images, which were applied to a time-series analysis of the spill.
MacDonald et al. (in review) Remote Sensing Assessment of Surface Oil Transport and Fate during Spills in the Gulf of Mexico, BOEM Report
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Surface volume: 12-h best estimate from SAR
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Average Volume (m3/km2)
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Sea-Trial of Subsea Dispersant Use • Responders were
stressed by HC fumes when working over the DWH site.
• A application of Corexit 95 into the subsea plume was tested on morning 10 May.
• Result was a temporary reduction of “thick” surface oil.
Lehr, W., S. Bristol and A. Possolo (2010). "Oil Budget Calculator Deepwater Horizon Technical Documentation." The Federal Interagency Solutions Group
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Time Series of DWH Oil Oil-Covered Water—all thicknesses
6 May ↓
23 May ↓
18 June ↓
18 July ↓
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Time Series of DWH Oil Oil-Covered Water—Thick Oil (~70 µm)
6 May ↓
23 May ↓
18 June ↓
18 July ↓
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Time Series of DWH Oil Daily SAR Volume of Surface Oil
6 May ↓
23 May ↓
18 June ↓
18 July ↓
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MacDonald et al. 2015 doi:10.1002/2015JC011062 Fig. 7
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Saildrone www.saildrone.com
• Autonomous surface sailor. • Solar power—extended
endurance • Intelligent steering • Near real-time reporting from
array of sensors • Challenging conditions in the
GoM—low wind, many obsticles
Daneshgar et al. Hindcast modelling for the persistence of floating oil slicks released from natural seeps. Remote Sensing Environ. (In review)
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Take-home ideas
• Remote sensing plays an essential role for detection and assessment of marine oil spills.
– Expansion of application could include routine satellite collections for monitoring at-risk areas.
• Satellite assets have fixed orbital schedules, which limit their tactical applications during response efforts.
– Relating oil thickness & chemical state to satellite images is an area where research and development is needed.
• Drone technology is highly promising, but needs field trials to make operational.