The Federal Oil Spill Team for Emergency Response Remote Sensing, FOSTERRS: Enabling Remote Sensing Technology for Marine Disaster Response

  • Ira Leifer
  • John Murray
  • Davida Streett
  • Timothy Stough
  • Ellen Ramirez
  • Sonia Gallegos


Oil spills cause significant to devastating ecological, economic, and societal damage, requiring years to decades for recovery. In cases of floods such as those associated with Hurricane Katrina, both oil and marine debris can enter the ocean, with debris posing its own hazards and ecological damage. In other cases, massive debris introduction can occur from natural causes such as the great Japanese tsunami in 2011.

These disasters demand the best available technology for response, damage mitigation, and remediation efforts. Disaster response remote sensing can play an important role by greatly leveraging available resources and assets and in mitigating consequences, as demonstrated during the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico. The extent and persistence of DWH overwhelmed traditional airborne observers, ability to monitor the spill’s development, with rapid response remote sensing filling critical response needs such as providing synoptic information on the spill. Still, incorporation of many remote sensing technologies faced significant challenges during the oil spill response.

To facilitate the sharing of remote sensing capabilities and to discuss improvements in disaster response, the Federal Oil Spill Team for Emergency Response Remote Sensing (FOSTERRS) interagency working group was created. Specifically FOSTERRS seeks to connect agency information on airborne and space borne asset’s availability, limitations, capabilities and performance, and ancillary data needs to stake holders and responders. FOSTERRS comprises members from agencies with remote sensing assets and key end users, while outreaching to the larger community involved in marine disaster response and the development and implementation of remote sensing best practices.


FOSTERRS Oil spill response Deepwater horizon 



Thanks are provided to the NASA Disasters Response Program of the NASA Applied Program, The NOAA’s Gulf of Mexico Disaster Response Center and NOAA National Environmental Satellite, Data, and Information Service (NESDIS), and the Naval Research Laboratory. Special thanks are also for Brenda Jones, US Geological Survey, for help in the manuscript preparation.


  1. Albaigés J, Morales-Nin B, Vilas F (2006) The prestige oil spill: a scientific response. Mar Pollut Bull 53:205–207CrossRefGoogle Scholar
  2. AP (1996) State postpones its plan to dump, burn oil in sea—Test delayed by fishermen’s concerns, logistics, Seattle Times. Seattle Times Company, SeattleGoogle Scholar
  3. ASCE (1996) State of the art review of modeling transport and fate of oil spill (task committee on modeling oil spills of the water resources engineering division). J Hydraul Eng 122:594–609CrossRefGoogle Scholar
  4. Bradley EB, Leifer I, Roberts DA, Dennison PE, Washburn L (2011) Detection of marine methane emission with AVIRIS band ratios. Geophys Res Lett 38:L10702CrossRefGoogle Scholar
  5. Byfield V (1998) Optical remote sensing of oil in the marine environment, School of Ocean and Earth Science. University of Southampton, Southampton, p 302Google Scholar
  6. Clark RN, Swayze GA, Leifer I, Livo KE, Kokaly R, Hoefen T, Lundeen S, Eastwood M, Green RO, Pearson N, Sarture C, McCubbin I, Roberts D, Bradley E, Steele D, Ryan T, Dominguez R, Team AAVIIS (2010) A method for quantitative mapping of thick oil spills using imaging spectroscopy, U.S. Department of the Interior, p 51Google Scholar
  7. Clester SM, Hornafius JS, Scepan J, Estes JE (1996) Quantification of the relationship between natural gas seepage rates and surface oil volume in the Santa Barbara Channel, (abstract). EOS Am Geophys Union Trans 77(46):F419Google Scholar
  8. Covello F, Battazza F, Coletta A, Lopinto E, Fiorentino C, Pietranera L, Valentini G, Zoffoli S (2010) COSMO-SkyMed an existing opportunity for observing the Earth. J Geodyn 49:171–180CrossRefGoogle Scholar
  9. Espedal HA (1999) Satellite SAR oil spill detection using wind history information. Int J Remote Sens 20:49–65CrossRefGoogle Scholar
  10. Estes JE, Senger LW (1971–1973) The multispectral concept as applied to marine oil spills. Remote Sens Environ 2:141–163CrossRefGoogle Scholar
  11. Fingas MF, Brown CE (1997) Review of oil spill remote sensing. Spill Sci Technol Bull 4:199–208CrossRefGoogle Scholar
  12. Fiscella B, Giancaspro A, Nirchio F, Pavese P, Trivero P (2013) Oil spill detection using marine SAR images. Int J Remote Sens 21:3561–3566CrossRefGoogle Scholar
  13. Garcia-Pineda O, MacDonald I, Hu C, Svejkovsky J, Hess M, Dukhovsky D, Morey SL (2013) Detection of floating oil anomalies from the Deepwater Horizon oil spill with synthetic aperture radar. Oceanography 26:154–137CrossRefGoogle Scholar
  14. Grierson IT (1998) Use of airborne thermal imagery to detect and monitor inshore oil spill residues during darkness hours. Environ Manag 2:905–912CrossRefGoogle Scholar
  15. HAZMAT (1996) Aerial observations of oil at sea, NOAA, H.M.R.a.A.D., April 1996, p 15Google Scholar
  16. Joye SB, MacDonald IR, Leifer I, Asper V (2011) Magnitude and oxidation potential of hydrocarbon gases released from the BP oil well blowout. Nat Geosci 4:160–164CrossRefGoogle Scholar
  17. Lehr B, Sky B, Possolo A, Allen AA, Boufadel M, Coolbaugh T, Daling P, Fingas M, French-McCay D, Goodmand R, Robert J, Khelifa A, Lambert P, Lee K, Leifer I, Mearns A, Overton E (2010) Oil budget calculator deepwater horizon: a report to the National Incident Command, November 2010, p 217.Google Scholar
  18. Leifer I, Luyendyk B, Broderick K (2006) Tracking an oil slick from multiple natural sources, Coal Oil Point, California. Mar Pet Geol 23:621–630CrossRefGoogle Scholar
  19. Leifer I, Lehr WJ, Simecek-Beatty D, Bradley E, Clark R, Dennison P, Hu Y, Matheson S, Jones CE, Holt B, Reif M, Roberts DA, Svejkovsky J, Swayze G, Wozencraft J (2012) State of the art satellite and airborne marine oil spill remote sensing: application to the BP deepwater horizon oil spill. Remote Sens Environ 124:185–209CrossRefGoogle Scholar
  20. McClimans T, Leifer I, Gjøsund SH, Grimaldo E, Daling P, Leirvik F (2013) Pneumatic oil barriers: the promise of bubble rafts. Proceedings of the Institution of Mechanical Engineers, Part M. J Eng Marit Environ 227:22–38Google Scholar
  21. Minchew B, Jones C, Holt B (2011) Polarimetric analysis of backscatter from the deepwater horizon oil spill using L-band synthetic aperture radar. IEEE Trans Geosci Remote Sens 50:3812–3830CrossRefGoogle Scholar
  22. NASA (2012) Technology Readiness Level, -.VDAbJSldVM2. Accessed 2014
  23. Ramirez-Marquez JE, Sauser BJ (2009) System development planning via system maturity optimization. Eng Manage, IEEE Trans 56:533–548CrossRefGoogle Scholar
  24. Reed M, Johansen O, Brandvik PJ, Daling P, Lewis A, Fiocco R, Mackay D, Prentki R (1999) Oil spill modeling towards the close of the 20th century: overview of the state of the art. Spill Sci Technol Bull 5:3–16CrossRefGoogle Scholar
  25. Salisbury JW, DʼAria DM, Sabins Jr FF (1993) Thermal infrared remote sensing of crude oil slicks. Remote Sens Environ 45:225–231CrossRefGoogle Scholar
  26. Sauser B, Ramirez-Marquez J, Verma D, Gove R (2006) From TRL to SRL: the concept of systems readiness levels. Conerence on Systems Engineering Research, Los Angeles, p 10Google Scholar
  27. Shen SS, Lewis PE (2011) Deepwater horizon oil spill monitoring using airborne multispectral infrared imagery, SPIE. SPIE, Orlando, pp 80480H-80481–80480H-80416Google Scholar
  28. Svejkovsky J, Lehr W, Muskat J, Graettinger G, Mullin J (2012) Operational utilization of aerial multispectral remote sensing during oil spill response: lessons learned during the deepwater horizon (MC-252) spill. Photogramm Eng Remote Sens 78:1089–1102CrossRefGoogle Scholar
  29. Topouzelis K, Karathanassi V, Pavlakis P, Rokos D (2007) Detection and discrimination between oil spills and look-alike phenomena through neural networks. ISPRS J Photogramm Remote Sens 62:264–270CrossRefGoogle Scholar
  30. Tseng WY, Chiu LS (1994) AVHRR observations of persian gulf oil spills, Geoscience and Remote Sensing Symposium, 1994. IGARSS ʼ94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation pp 779–782Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Ira Leifer
    • 1
    • 2
  • John Murray
    • 3
  • Davida Streett
    • 4
  • Timothy Stough
    • 5
  • Ellen Ramirez
    • 4
  • Sonia Gallegos
    • 6
  1. 1.Bubbleology Research InternationalSolvangUSA
  2. 2.University of CaliforniaSanta BarbaraUSA
  3. 3.National Aeronautic and Space Agency, Langley Research Center, NASA, LRCHamptonUSA
  4. 4.National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information ServiceNOAA, NESDISCollege ParkUSA
  5. 5.Jet Propulsion Laboratory, JPLPasadenaUSA
  6. 6.Naval Research Laboratory, NRL, Stennis Space CenterHancock CountyUSA

Personalised recommendations