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Remote Sensing Systems to Detect and Analyze Oil Spills on the

US Outer Continental Shelf – A State of the Art Assessment

Final Report

31 Jan, 2016

Authors: Derek Burrage (P.I.)*, Sonia Gallegos, Joel Wesson, Richard Gould, Richard Crout and Sean McCarthy.

Ocean Sciences Branch, Naval Research Laboratory, Stennis Space Center, 39529, MS, USA.

Acknowledgement

This study was funded by the U.S. Department of the Interior, Bureau of Safety and Environmental Enforcement through Interagency Agreement E14PG00058 with the Naval Research Laboratory.

Caveat

This final report has been reviewed by the BSEE and approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the BSEE, nor does mention of the trade names or commercial products constitute endorsement or recommendation for use.

*Contact Phone: (228) 688 5241 (W) (985) 285 9563 (C) Email: derek.burrage@nrlssc.navy.mil

______________________________________________________________________________________

BAA for Research on Oil Spill Response Operations in the U.S. OCS

BSEE Project Number: E14PS00011

Topic: Oil Spill Detection and Analysis Using Remote Sensing Technologies.

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Table of Contents Executive Summary .................................................................................................................................................................. 3

Approach .................................................................................................................................................................................. 3

Major Outcomes ....................................................................................................................................................................... 5

Comprehensive literature review ......................................................................................................................................... 5

Sensor Selection Tool ........................................................................................................................................................... 6

Sensor Electromagnetic Spectrum ....................................................................................................................................... 6

Use of Oil Weathering and Trajectory Models ..................................................................................................................... 7

Conference Participation ...................................................................................................................................................... 8

Recommendations ................................................................................................................................................................... 9

Project Documentation ...................................................................................................................................................... 12

References .......................................................................................................................................................................... 13

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Executive Summary

Efficient and rapid detection of oil spills that occur over the continental shelf is vitally important for a host of societal, environmental, economic and public safety reasons. However, the variety of spill sizes and types, coupled with the dynamic environment of a spill, its rapidly evolving physical and chemical characteristics and changing weather conditions, makes detection and analysis using remote sensing methods challenging. This final report summarizes the results of the BSEE-funded project “Remote Sensing Systems to Detect and

Analyze Oil Spills on the US Outer Continental Shelf – A State of the Art Assessment.” The goal of the project

was to analyze and report on state-of-the-art technologies for the detection and analysis of oil spills on the US

outer continental shelf (OCS). Related sub-goals were: 1) Develop a set of evaluation criteria for the

technology. 2) Construct scenarios describing a variety of possible continental shelf oil spill sizes and types. 3)

Survey and assess the technology. 3) Evaluate the sensor technology against the selection criteria with respect

to specified scenarios.

This assessment is motivated by the need for oil spill response planners and operators to have up-to-date

information on available and developing technologies and systems for oil spill detection and analysis. These

systems must meet their needs in a variety of spill scenarios, and under various observational conditions

(including the expected meteorological and oceanographic conditions and, if known, the disposition and

physico-chemical condition of the oil), as well as logistical and resource constraints.

Approach

To meet the project goals, a comprehensive assessment and evaluation of the capabilities and limitations of

current oil spill detection and analysis systems for use in offshore oil and gas operations on the US OCS was

conducted. This assessment considered a range of operational and experimental systems that are currently in

use, or under development, and their practicality under different oil spill scenarios.

The evaluation considered both the intrinsic performance of remote sensing technologies for detecting oil

spills and their suitability for application to particular oil spill types and conditions. It defined and considered

the key technical specifications of the sensors, including their strengths and weaknesses, as well as the

hardware, operational and logistical requirements, and their deployment and use. It further considered data

acquisition and delivery options and, where available, hardware and data costs.

It was conducted using a custom designed interactive sensor selection tool, the Instruments to Detect and

Analyze Oil Spills, IDAOS, spreadsheet system. IDAOS was developed with the dual purpose of providing a

sensor selection tool that can be used immediately by the project team to conduct the sensor survey and

evaluation, and subsequently by oil spill responders and remote sensing professionals for a variety of possible

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applications, such as education and training exercises and, after suitable testing and refinement, selecting

sensors to be used in remote sensing missions for operational spill response.

The final evaluation of preferred sensors was performed by positing a representative set of ‘deployment

modes’ or ‘mission types’ spanning a variety of oil spill types and conditions, and based on a customized list of

remote sensing applications. To facilitate and simplify the definition of these missions, broad categories for

factors including spill size and duration and geographical context (water body type) were defined and

tabulated. This facilitated the inclusion of a small number of spills (both historical and hypothetical) to help

define the constraints and scope of each of the missions. For each mission, and relevant scenarios selected

using the spreadsheet system, the sensor selection and scenario tool (specifically, the spreadsheet interactive

Sensor/Scenario Matrix) was used to find those ‘preferred’ sensors that rated highest in terms of their intrinsic

performance and suitability for that mission.

Recommendations on preferred sensors to meet such mission requirements were then put forward and

discussed. Such recommendations could be employed or adapted to help plan remote sensing deployments for

purposes other than emergency spill response. One of several examples, which are explored in the technical

report, relates to planning of oil platform mounted monitoring systems comprising a suite of sensors for early

detection of oil spills and real-time notification. With the possible exception of marine radar systems, which

have demonstrated capabilities for oil spill detection around ships and oil rigs, and a small number of

operational multi- and hyper-spectral sensors, there are few examples of sensors specifically designed and

configured to meet the requirements of a comprehensive oil spill monitoring system. Application of the sensor

selection tool for this type of mission suggests that a sensor suite comprising both optical (infra-red, visible)

and microwave sensors would be needed to provide a system that can reliably detect and report oil spills in all

weather conditions. The attempt to identify sensors that would be well suited to this application led to the

development of a set of desirable characteristics of an on-platform monitoring system, which could be the

subject of future investigations.

Additional ancillary tasks were also performed using the sensor selection tool. For example, a list of selected

sensors which were found using the sensor performance score to be among the best performers in their class

was constructed. These classes were based on technology Categories and Sub-categories, among other

groupings that were previously defined and tabulated in preparation for data base entry. The sensor selection

tool might thus find application in manufacturer product development, to help identify instrument

specifications that are considered significant for oil spill response applications.

Project deliverables, which complement and support this final report include a comprehensive technical

report, Burrage et al., (2016, henceforth, ‘the Technical Report’), a spreadsheet-based sensor selection tool

with an interactive user interface, a sensor selection guide (describing the sensor selection tool and its use, to

be found in the Technical Report, Pt 4 and Appendix), and a journal article (in preparation) detailing the

methodology and findings of the project.

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Major Outcomes

Comprehensive literature review

A comprehensive review of the literature on the technology for remote sensing of oil spills was conducted. This

was performed in order to: a) Devise a set of instrument specifications and criteria for evaluating sensor

performance and suitability. b) Determine appropriate values for these criteria and specifications for entry into

the data base. c) Produce a selection of references, reports and web sites that could be used for additional

information on sensor performance and previous applications to oil spill detection and analysis. This review

spanned over 170 documents, mostly in the form of journal articles and reports that were considered relevant

to the task. Among these approximately 85 were adopted for use as key references that can be accessed from

inside the sensor selection tool (Caveat: copyright restrictions might restrict access for particular articles and

users). In addition approximately 60 background documents were collected to provide specific information on

sensors and historical spills, among other topics.

The literature review commenced with a technical review produced 20+ years ago (Fingas, 1991) as part of the

Technology Assessment Program (TAP) project # 154. This review, released soon after the 1989 Exxon Valdez

oil spill in Prince William Sound, Alaska, provided a useful reference against which to assess more recent

progress. It considered both optical and microwave technologies and has been updated several times (most

recently in Fingas and Brown (2014). Other reviews published in the intervening period include Goodman

(1994), Brown and Fingas (2003), Brekke and Solberg (2005) and Jha et al (2008), and Fingas and Brown (2012).

Some of these were applied to particular geographic conditions or regions. Puestow et al., 2013, which focused

on spill detection and mapping in low visibility and ice under conditions found in the Arctic, could also be

applicable to the Alaskan shelf. The review by Leifer et al. (2012), which surveyed the sensors deployed during

the 2010 BP Deep Water Horizon (DWH) Oil Spill in the Gulf of Mexico, focused primarily on optical

technologies, but also discussed active radar systems. The planning guidance on remote sensing to support oil

spill response provided in the American Petroleum Institute (API, 2013) surveyed the principal types of remote

sensing technology that are appropriate for this purpose. Using a primary classification based on visual

observation, active/passive sensors and multi-band and multi-sensor integration, the report advocated sensor

selection based on oil spill response mission goals and prevailing conditions. Two recent reports, which survey

and assess surface surveillance capabilities for oil spill response using satellite and airborne remote sensing by

Partington (2014a,b) supplement and expand on the many previous reviews and comparisons of remote

sensing instrumentation for oil spill response that have been prepared over the last quarter century.

The literature review and web search produced a large number of web-links and web-based documents. The

results are accessible through the sensor selection tool, so users wishing to access details of sensors and

scenarios that are not actually tabulated in the data base system can access additional background

information. Among its several features, the sensor selection tool effectively encapsulates the information

contained in the various reviews mentioned above, in the form of sensor specifications and criteria that are

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built into the data base tables. They are thus readily accessible and updatable, as new sensors and scenarios

are identified and entered into the data base system.

Sensor Selection Tool

The spreadsheet sensor selection tool includes the following key components:

A searchable sensor technology data base, populated with a variety of remote sensing instruments

selected for their potential or demonstrated application to detect oil spills or relevant environmental

variables.

An oil spill scenario data base populated with historical, hypothetical and user-defined spill information.

Supporting tables that contain specifications and criteria determining instrument performance,

citations and links to references that describe the hardware and associated data products, names and

site links for hardware and data suppliers, and oil types.

An interactive sensor/scenario matrix that links the information available in the two data bases, to

produce an evaluation of the intrinsic performance of the sensors and their suitability for application to

particular oil spills.

Interactive sensor and scene selection spreadsheets that display the key features and facts describing

the various sensors and spills in the data base.

The spreadsheet system is fully interactive. It takes advantage of Excel’s built in filtering, sorting and searching

capabilities and uses custom Visual Basic modules to propagate the results of these filtering and search

operations to the interactive spreadsheets described above.

In addition, a browser-based sensor selection ‘Demo’ tool, which utilizes the spreadsheet data base, was

developed as a prototype for a full-fledged on-line sensor selection system that could be developed in a future

project.

Sensor Electromagnetic Spectrum

The portions of the electromagnetic (E-M) spectrum that the sensors can span (sensor spectral wave bands)

have a significant effect on the capabilities of the sensor for detecting oil or related chemical, biological or

physical oceanographic or atmospheric properties. To a large extent, they also determine their suitability for

use in different seasons, at different times of day, or under prevailing weather and sea state conditions. It is

thus useful to be able to quickly assess where particular sensor measurement channels fall within the E-M

spectrum, and the widths of the channels that they span. A graphical display of the E-M spectrum with the

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currently selected sensor wave bands superimposed on it, appears in the SpectrumTable spreadsheet of the

IDAOS sensor selection tool, and a sample spectrum graph appears in the Technical Report.

The IDAOS Instrument Table spreadsheet includes a table showing the Primary through Quaternary wave

bands, in units of wavelength (microns) or equivalent frequency (GHz). The table entries are automatically

transcribed from the relevant Instrument Table entries to the Spectrum Table spreadsheet. Separate graphs

with differing wavelength or frequency spans appear beneath that table (See technical report for details).

These graphs allow the user to quickly view, compare and assess the E-M bands measured by all the sensors in

the data base (arranged horizontally in each graph) or the current subset, as determined by applicable filtering

or sorting operations.

Use of Oil Weathering and Trajectory Models

To help develop hypothetical spill scenarios and fill gaps in the spill parameter space spanned by the historical

spills, the NOAA ADIOS and GNOME spill prediction models were used. In particular, the ADIOS and GNOME

models where used to a develop the ‘Long Is Sound’ hypothetical spill, and the much smaller 2 bbl ‘Oil Rig 2’

hypothetical spill, as described below:

A combination of ADIOS2 and GNOME simulation runs was conducted for a relatively small (1000 bbl)

hypothetical oil spill in eastern Long Island Sound. The model input parameters, which include spill size and

date, oil type and prevailing weather conditions, among other factors were defined in a consistent manner for

both models. This enabled both their complementary output features to be exploited to provide a

comprehensive assessment of the spill. The example chosen was that described in the GNOME user guide,

which includes use of the Central Long Island Sound Location File.

An ADIOS oil weathering model simulation was run for an instantaneous spill of 2 bbl (the minimum the

model will accept!) of GOM Green Canyon Block 109 crude into water of 20 deg C, salinity 32 psu and

sediment load 5 gm-3,under a steady 1 ms-1 wind. After 12 hr, the amounts evaporated and dispersed, and the

water content, were 26.6 and 4.6 %, and 78 %, respectively, so there was 70% or 1.4 bbl remaining,

presumably on the water surface. Under the same scenario, running the GNOME oil trajectory model, which

also accounts for oil weathering (but only, in this case, as generic medium crude oil), shows that after 12 hr

the oil has spread into a nearly circular plume with a diameter of about 2 Nm (3.7 km).

The combined ADIOS and GNOME spill simulation data detailed above and other consistent assumptions were

thus used to construct the user defined Scenarios ‘Long Island’ (Scenario #11) and ‘Oil Rig 2’ (#25) in IDAOS.

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Conference Participation

Early in the project, the P.I. (D. Burrage) participated in the 2015 Gulf of Mexico Oil Spill and Ecosystem Science

Conference in Houston, TX from 15-19 Feb., 2015. This included presentation of a poster paper, gathering

feedback from attendees, and attendance at other sessions. The poster described the plan and current status

of the project. A report was prepared documenting the relevant outcomes of the conference, with an emphasis

on the oil spill remote sensing aspects (See report, submitted previously).

The P.I. also participated in the S&T NRT teleconference of April 14, 2015. He presented a verbal summary of

the project and provided a copy of our GOMRI 2015 Gulf of Mexico Oil Spill and Ecosystem Conference poster

paper. Following the summary, plans regarding preparation of Fact Sheets and an online data base were briefly

discussed. Strong interest was expressed in the possible development of an online system taking the form of a

sensor selection tool, similar in scope and function to an existing NRT Selection Guide used to choose

appropriate oil spill mitigation strategies (http://nrt-sg.sraprod.com/build/#).

The production of Fact Sheets has been pursued to the extent that the IDAOS Select Sensor and Select Scene

spreadsheets have been developed to provide a ‘snap shot’ of the key parameters of any sensor contained in

the data base. This information can be combined with the more generic descriptions of sensor categories and

types provided in the Technical Report, Pt2 to compile and print a profile describing sensors of interest. (This

process could be more fully automated to allow printable Fact Sheets to be generated on demand in a future

version of IDAOS).

The P.I. participated in the Oil Observing Workshop held 20-22 Oct., 2015 at NOAA’s Gulf of Mexico Disaster Center. The need for tools to help oil spill professionals and first responders to identify and select from available remote sensing technologies for spill response and remediation was put forward and discussed independently by several of the breakout groups and by various individuals during the workshop. When presented as an example of the required methodology and decision tools, NRL’s BSEE-supported work was enthusiastically received by the participants. The resulting discussion indicates that further development efforts to generate well designed and tested ‘Job aids’ for operational use before, during and in the aftermath of oil spills, is justified to support the needs of personnel from multiple agencies and industry who are concerned with emergency response, damage assessment and training, among other potential applications.

As the project neared completion, the P.I. participated in the ICCOPR teleconference of Dec 16, 2015. He gave

a powerpoint presentation summarizing the project and demonstrated both the IDAOS Excel spreadsheet

system and the browser-based Demo of the Sensor Selection tools developed during the project. Supportive

comments were received from the Committee chair William Volcke and participant Scot Lundgren of NOAA.

There were also questions concerning the scoring system and database sorting features by Robyn Conmy and

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Steve Lehman, respectively. A subsequent email exchange, which included comments by Robyn, Steve and Lori

Medley further clarified our response to these questions.

Recommendations

A number of recommendations for future actions can be drawn from the project results and outcomes. These fall

naturally into four main groups as follows:

1) Development of standardized mission applications and plans, based on preferred sensor packages and

suites, to enable rapid deployment of appropriate remote sensing technologies in common spill

scenarios.

To facilitate contingency planning for responses to futures oil spills, identification of preferred sensors for application to

specified response goals and spill types and, in certain circumstances or in vulnerable geographic areas, forward

deployment of remote sensing platforms and sensor suites, could significantly streamline and accelerate the response.

There is currently interest in identifying types of missions that could be needed for Airborne Unmanned Systems, AUV,

use in particular (Stephen Lehmann, NRT, personal communication), and this could be broadened to encompass all types

of oil spill remote sensing mission (at least those likely to require any of the airborne platforms).

As a demonstration of the sensor evaluation process, and with the intention of providing guidance to users on potential

applications of the sensor selection tool, the following sensor evaluation procedure was performed: First five

representative deployment modes or mission types were identified, based on specified spill remote sensing applications,

representative scenarios falling within broad categories of spill type, geographic context, volume and size, and prevailing

conditions. For each mission, the Sensor/Scenario Matrix embedded in IDAOS was then used to identify a list of preferred

sensors with acceptable Performance Scores and the highest Suitability indices for the relevant spills (see Technical

Report Table 11 for details).

2) Development of integrated sensor suites designed for detecting and analyzing oil spills from specific

remote sensing platforms to support standardized oil spill monitoring and response missions.

It is recommended that a list of standard mission types be developed for application to representative

historical or hypothetical oil spills, to allow preferred sensors meeting mission requirements to be

identified, as an aide to planning future remote sensing deployments.

Evaluate the available sensors with respect to types of spill scenario that are amenable to a standardized set of

remote sensing missions and adopt preferred sensors for specific deployment modes or missions, based on the

available sensors and relevant historical or hypothetical spill scenarios.

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One of the five deployment modes considered in this demonstration that is of particular interest in the regulatory and

enforcement context, concerns Monitoring from Oil Platforms. However, application of the sensor selection tool

revealed that few sensors and no commercially available sensor suites are currently available to meet this need in an

economical and reliable fashion. Of the sensors identified, several of the marine radars, which are specifically configured

for oil spill detection, and only a couple of the optical sensors could meet the minimal requirements of this deployment

mode.

Initiate a research effort to design and develop an integrated sensor package that combines sensors

operating in the Visible, IR and Microwave part of the spectrum, to meet the requirements of an oil

platform-mounted monitoring system.

3) Field-testing and enhancement of the sensor selection tools, and periodic updating of the underlying

data bases, to make them available to future users with a diverse range of computing platforms,

applications and needs.

In reference to the sensor selection tools developed for this project, a list of six technical recommendations relating to

their testing and further development was proposed (See Technical Report Part 5. Technical Recommendations for

details). Of these, two that are considered key to future and related developments are given below:

Make the IDAOS spreadsheet system and associated user guide available for testing and evaluation by

selected oil spill remote sensing users and other oil spill professionals. Invite feedback on all aspects of

system use to identify usability issues, and additional features or refinements that might be developed

to improve its functionality and utility.

Based on the needs expressed during the recent Oil Observing Workshop, held on 20-22 Oct., 2015 at NOAA’s

Gulf of Mexico Disaster Response Center (see OilObservingWorkshop_report1h.pdf), a list of desirable

characteristics for a Job Aid that provides a sensor selection capability was compiled (See Technical Report

Conclusions and Recommendations for details). These could provide a reference point for continued

development and expansion of the capabilities of the IDAOS, and prototype browser-based, sensor selection

tools developed for this project and described above, in order to produce a comprehensive multi-platform

sensor selection tool.

Undertake a design and development study, based on the experience and user feedback obtained from

desk studies and field testing of the IDAOS Excel spreadsheet system, and on user feedback from the

prototype browser-based Demo, to specify requirements for, and develop the capabilities of, a

comprehensive web-based multi-platform sensor selection tool.

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4) Enhancement and updating of the sensor and scenario database to expand its utility.

While the NOAA GNOME and ADIOS oil spill prediction models can be used in a complementary fashion as described in

the Part 2 of the technical report, a more comprehensive model that incorporates trajectory, weathering and spill budget

information in one system would be easier to apply for the purpose of developing hypothetical spill scenarios for

assessing remote sensing technologies.

Develop a procedure for regular updating of the Sensor selection tool Instrument and Scenario

databases to a ensure that new sensors and sensor technologies are included, and that a wide range of

representative historical and hypothetical spills are available for evaluating them. A frequent updating

interval of less than 3 to 6 months is recommended.

Test, evaluate and enhance the available oil spill weathering and trajectory prediction models, and

utilize their capabilities to construct new hypothetical spill scenarios for inclusion in the Scenario

database.

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Project Documentation

Burrage, D., R. Gould, S. Gallegos, J. Wesson and S. McCarthy (2014a) ”Remote Sensing Systems to Detect and Analyze Oil

Spills on the US Outer Continental Shelf – A State of the Art Assessment” BSEE E14PG00058 Technical proposal, pp. 41,

(NRL Oceanography, Stennis Space Center), BSEE_E14PS00011_OilSpill_NRL_TechnicalProposal.pdf

Burrage, D., S. Gallegos, J. Wesson, R. Gould and S. McCarthy (2014b) "Remote Sensing Systems to Detect and Analyze

Oil Spills on the US Outer Continental Shelf – A State of the Art Assessment". Power Point presentation, Slides: 21. (NRL

Oceanography, Stennis Space Center), BSEE_OilSpillRemSensing_Plan_Burrage_etal_E14PG00058.pptx).

Burrage, D., R. Gould, S. Gallegos, J. Wesson and S. McCarthy (2014c) "Remote Sensing Systems to Detect and Analyze Oil

Spills on the US Outer Continental Shelf – A State of the Art Assessment". (BSEE/NRL IA: E14PG00058). Meeting Report

(NRL Oceanography, Stennis Space Center), pp. 5. (NRL Oceanography, Stennis Space Center),

BSEE_OilSpillRemSensing_E14PG00058_KickOffMeeting_10Nov2014subm_corr.docx

Burrage, et al. (2014d) "Evaluation of recent reports on assessing surface surveillance capabilities for oil spill response

using satellite and airborne remote sensing by Partington 2014a,b". pp. 7. (NRL Oceanography, Stennis Space Center),

BSEE_OilSpillStudy_Scope_Response_Burrage2subm.pdf

Burrage, D. M. and J. Wesson (2015) “Report on Phone Conference with BSEE 9 Jan., 2015 concerning Oil Spill Remote

Sensing project Scope”. 14 Jan., 2015. pp. 5. (NRL Oceanography, Stennis Space Center),

BSEE_E14PS00011_OilSpill_NRL_PhoneConfReport_09Jan2015c_Subm.pdf

Burrage, D. M., S. C. Gallegos, J. C. Wesson, R. W. Gould, S. C. McCarthy (2015a) " Remote Sensing Systems for Oil Spill

Detection and Analysis – A State of the Art Assessment”. Abstract 2015-A-433-GOMRI, 2015 Gulf of Mexico Oil Spill and

Ecosystem Science Conference (Houston, TX). (Burrage_etal_OilSpillRemSensing.pdf)

Burrage, D. M., S. C. Gallegos, J. C. Wesson, R. W. Gould, S. C. McCarthy (2015b) " Remote Sensing Systems for Oil Spill

Detection and Analysis – A State of the Art Assessment”. Poster Paper # 129, Session 11, Thur 18 Feb., 2015 Gulf of

Mexico Oil Spill and Ecosystem Science Conference (Houston, TX).

(Burrage_OSEC_2015_BSEE_SensorEval2k_Resize1.pdf)

Burrage, D. M. (2015a) “Report on Attendance at 2015 Gulf of Mexico Oil Spill and Ecosystem Science Conference” 16-19

Feb., 2015 (Houston, TX). 4 Mar., 2015. pp. 8. (NRL Oceanography, Stennis Space Center) ,

OilSpill&EcosystemScienceConf_report3.pdf

Burrage, D. M. (2015b) “Report on Attendance at Oil Observing Workshop held 20-22 Oct., at NOAA’s Gulf of Mexico

Disaster Response Center”. pp. 10. (NRL Oceanography, Stennis Space Center), OilObservingWorkshop_report1h.pdf

Burrage, D. M., R. Gould and S. McCarthy (2015) “Remote Sensing Systems to Detect and Analyze Oil Spills on the US

Outer Continental Shelf – Decision Tools. Meeting Report”, pp. 8. BSEE, New Orleans, 30 Nov. 2015, (NRL Oceanography,

Stennis Space Center), BSEE_E14PS00011_OilSpill_NRL_DecisionTools_MeetingReport1a.pdf

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Burrage, D., S. Gallegos, J. Wesson, R. Gould, R. Crout and S. McCarthy (2016) ”Remote Sensing Systems to Detect and

Analyze Oil Spills on the US Outer Continental Shelf – A State of the Art Assessment” BSEE E14PG00058 Technical Report,

(NRL Oceanography, Stennis Space Center). pp. 100 (BSEE_E14PS00011_OilSpill_NRL_TechnicalReport.pdf)

References

API (2013) “Remote Sensing in Support of Oil Spill Response: Planning Guidance” (American Petroleum

Institute) Technical Report 1144, Sept. pp 32. Brown, C. E. and Fingas, M. F. (2003) “Review of the development of laser fluorosensors for oil spill

application” Marine Pollution Bulletin, v 47, p 477-484. Brekke, C. and Solberg Anne H. S. (2005) “Oil spill detection by satellite remote sensing” Remote Sensing of

Environment, v 95 p 1-13. Fingas, M. F. (1991) “Oil Spill Remote Sensing: A Review” pp 24. A report Prepared by the Chevron Oil Spill

Workshop: Sept 24-27, 1991, San Francisco, California (Technology Assessment Programs project #154. Fingas, M. and Brown, C. (2012) “Oil Spill Remote Sensing”. In Meyers R. A. (Ed) Encyclopedia of Sustainability

Science and Technology, pp 7491-7527. Fingas, M. and Brown, C. (2014) “Review of oil spill remote sensing”. Marine Pollution Bulletin, v 83, p. 9-23.

Goodman, R. (1994) “Overview and future trends in oil spill remote sensing” Spill Science and Technology Bulletin, v 1 n 1 p11-21. (Abstract, full text not sighted)

Jha, M. N., J. Levy and Y. Gao (2008) “Advances in Remote Sensing for Oil Spill Disaster Management: State-of-

the-Art Sensors Technology for Oil Spill Surveillance” Sensors v 8, p 236-255. Leifer et al. (2012) “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP

Deepwater Horizon oil spill.” Rem. Sens. Env. v 124, p 185-209. Partington (2014a) “An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Satellite

Remote Sensing” 10 April, Polar Imaging Limited, Andover, Hampshire, UK SP11 0BA, Reference PIL-4000-35-TR-1.2, pp. 63.

Partington (2014b) “An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne

Remote Sensing. 21 May, Polar Imaging Limited, Andover, Hampshire, UK SP11 0BA, Reference PIL-4000-38-TR-1.0., pp. 83.

Puestow et al., (2013) “Oil Spill Detection and Mapping in Low Visibility and Ice: Surface Remote Sensing” Final

Report 5.1, Arctic Oil Spill Response Technology Joint Industry Program.