Fahad Alawadi,1 Carl Amos,2 Valborg Byfield,3 Peter Petrov1
1Regional Organization for the Protection of Marine Environment (Kuwait) 2Univ. of Southampton (United Kingdom) 3National Oceanography Ctr. (United Kingdom)
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Oil spills pose a serious threat to the sensitive marine ecosystem of the RSA. The study aims to detect and identify oil
spills using remote sensing data provided by ROPME MODIS receiving station. MODIS data of confirmed incidents of
oil spills via in-situ observations were processed to produce radiometrically corrected L1B data. Algal mats were further
eliminated as look-alike, when the distinct oil pattern was not visible in the standard MODIS algorithm for Chlorophyll
a. Shape analysis based on the operators' prior knowledge of the region was also used as a method for discriminating oil
from other look-alikes. Oil spills exhibit different levels of contrast in relation to the viewing angle geometry and sun
position. The Spectral Contrast Shift (SCS) is an empirical relationship that was derived to identify sea surface patterns
including oil spills using the maximum and minimum spectral radiance values at the 250m spatial resolution bands.
Results were combined with GIS based information of oil platform locations and daily tanker routes to aid interpretation
and improve the probability for an accurate identification of oil spills, and avoiding false positives.
Fahad Alawadi,Carl Amos,Valborg Byfield, andPeter Petrov
"The application of hyperspectral image techniques on MODIS data for the detection of oil spills in the RSA", Proc. SPIE 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, 71100Q (10 October 2008); https://doi.org/10.1117/12.799374
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Fahad Alawadi, Carl Amos, Valborg Byfield, Peter Petrov, "The application of hyperspectral image techniques on MODIS data for the detection of oil spills in the RSA," Proc. SPIE 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, 71100Q (10 October 2008); https://doi.org/10.1117/12.799374