The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XXXIX-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 63–66, 2012
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 63–66, 2012

  31 Jul 2012

31 Jul 2012


B. Osmanoğlu1, C. Özkan2, F. Sunar3, and G. Staples4 B. Osmanoğlu et al.
  • 1University of Alaska - Fairbanks, P.O. Box 757320, Fairbanks, AK 99775
  • 2Erciyes University, Engineering Faculty, Geodesy and Photogrammetry Engineering Dept., 38039 Kayseri,Turkey
  • 3Istanbul Technical University, Civil Engineering Faculty, Geomatics Engineering Dept., 34469 Maslak Istanbul, Turkey
  • 4MDA, 13800 Commerce Parkway, Richmond, V7S 1L5, Canada

Keywords: Marine pollution, Oil spill detection, Probability map, SAR

Abstract. The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m3 of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries.

For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellitebased oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR) satellites are a major contributer of monitoring marine environments for oil spill detection.

We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band), Envisat ASAR (C-band) and Alos-PALSAR (L-band) sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days) allow us to eliminate artifacts and increase accuracy.

Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.