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TitleThe Influence of Surface Oil On C- and Ku-Band Ocean Backscatter
 
AuthorSingh, K P; Gray, A L; Hawkins, R K; O'Neil, R A
SourceIEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) vol. GE-24, issue 5, 1986 p. 738-744, https://doi.org/10.1109/tgrs.1986.289622
Year1986
Alt SeriesEarth Sciences Sector, Contribution Series 20040565
Alt SeriesRESORS 1054251
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
SubjectsScience and Technology; remote sensing; satellites; satellite imagery; oil; oil spills; radar imagery; Radarsat; ERS-1
AbstractA comparative study of ocean backscatter depression due to surface oil has been carried out using Ku-and C-band scatterometers supported by some X-and C-band synthetic aperture radar (SAR) imagery. The depression of radar backscatter for both C-and Ku-band HH-polarized radiation has been measured for the incidence angle range from 20° to 50° on two days, September 16 and 17, 1983 on which the average wind and wave height conditions were 3-6 m/s, 0.3 m and ~10-14 m/s, 1.2 m, respectively. Results show that the depression in Ku-band backscatter increases from approximately 3-5 dB at 20° to ~10 dB or more at 30°-40° and then decreases at the larger incidence angles. Generally, the angular dependence of C-band backscatter depression was similar to that at Ku-band, but the peak depression was shifted to slightly larger angles and usually exceeded Ku peak 1-2 dB. The Ku-band results are in good agreement with previous work [9] that tentatively explained the angular results of backscatter depression on the basis of a selective damping of the first-order Bragg resonant waves by the oil film. This explanation, however, is inconsistent with the results of the present work when both C-and Ku-band are considered. The significance of the data is discussed in the context of present and future radar systems (e. g., the ESA ERS-1 SAR and the Radarsat SAR).
GEOSCAN ID217367

 
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