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A Sensitivity Analysis of the Standard Deviation of the Copolarized Phase Difference for Sea Oil Slick Observation.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; Apr2019, Vol. 57 Issue 4, p2022-2030, 9p
- Publication Year :
- 2019
-
Abstract
- In this paper, a time series of 33 TerraSAR-X copolarized synthetic aperture radar (SAR) imagery collected in Stripmap mode over the Gulf of Mexico in a wide range of incidence angles and sea-state condition is exploited, together with a theoretical framework based on the X-Bragg scattering model, to analyze the effects of noise, angle of incidence, (AOI) and wind speed on the standard deviation of the copolarized phase difference ($\sigma _{\phi _{c}}$) evaluated over sea surface with and without oil slicks. This large data set represents an unprecedented opportunity to analyze, for the first time, the influence of both SAR acquisition and surface parameters on the broadening of the copolarized phase difference probability density function (pdf), $p_{\phi _{c}}(\phi _{c})$. Experimental results show that the X-Bragg scattering model, here adopted to predict the sea surface $p_{\phi _{c}}(\phi _{c})$ , gives an understanding of the increasing trend of $\sigma _{\phi _{c}}$ with respect to AOI. It is shown that the noise significantly contributes to broaden $p_{\phi _{c}}(\phi _{c})$ over both slick-free and slick-covered sea surface, while the effects of low-to-moderate wind regimes are negligible. In addition, $\sigma _{\phi _{c}}$ exhibits a larger sensitivity to the scene variability, if compared to single-polarization intensity channels, over both slick-free and oil-covered sea surface. This sensitivity is more pronounced at lower AOIs due to the higher noise equivalent sigma zero (NESZ) that affects larger AOIs. [ABSTRACT FROM AUTHOR]
- Subjects :
- SYNTHETIC aperture radar
WIND turbines
REMOTE sensing
POLARIMETRY
OCEAN temperature
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 57
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 136509050
- Full Text :
- https://doi.org/10.1109/TGRS.2018.2870738