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Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
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Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
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Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function

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Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function
Journal Article

Wave retrieval from quad-polarized Chinese Gaofen-3 SAR image using an improved tilt modulation transfer function

2024
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Overview
An accurate Modulation Transfer Function (MTF) is essential for Synthetic Aperture Radar (SAR) wave spectra retrieval. This study aimed to investigate the performance of a quad-polarized wave retrieval algorithm based on fully polarimetric SAR image data using the improved tilt MTF and considering the influence of wind speed. The tilt MTF is the key factor in the wave retrieval scheme from quad-polarized (Vertical-Vertical (VV), Horizontal-Horizontal (HH), Vertical-Horizontal (VH), and Horizontal-Vertical (HV)) SAR images. In this study, the waves were inverted from more than 1300 Gaofen-3 (GF-3) images acquired in quad-polarization strip mode with a spatial resolution of 16 m and a swath coverage of 50 km. The winds were retrieved using the Geophysical Model Function (GMF) C-band SAR model for Gaofen-3 (CSARMOD-GF), which is suitable for re-calibrated GF-3 images in VV-polarization. The comparison of the wind speed yielded a Root Mean Square Error (RMSE) of 1.73 m/s and a Correlation Coefficient (COR) of 0.94. The validation of the Significant Wave Height (SWH) simulated using the Waves Nearshore (SWAN) model against Haiyang-2B (HY-2B) altimeter data yielded an RMSE of 0.56 m and a COR of 0.87. The results reveal that the SAR-derived wind and SWAN-simulated SWH are suitable for analysis of SAR wave retrieval. The full polarimetric technique was applied to the collected images, and the statistical analysis yielded a RMSE of 0.51 m, a COR of 0.75, and a Scatter Index (SI) of 0.44 compared with the SWHs retrieved using the simulations from the SWAN model. The non-polarized contribution in the Normalized Radar Cross Section (NRCS; unit: dB) caused by wave breaking $\\sigma _{\\rm{0}}^{wb}$ σ 0 w b was calculated using a theoretical approach that employs the VV-polarized calibrated NRCS $\\sigma _{\\rm{0}}^{{\\rm{vv}}}$ σ 0 v v and HH-polarized calibrated NRCS. The effect of wave breaking on the SAR retrieval waves was studied. The bias (SAR-derived minus SWAN-simulated SWH) increased as the ( $\\sigma _{\\rm{0}}^{wb}$ σ 0 w b / $\\sigma _{\\rm{0}}^{{\\rm{vv}}}$ σ 0 v v ) ratio (>0.4) increased, and the accuracy improved when the ratio was less than 0.4. This behavior is reasonable since the wave breaking inevitably affects the tilt modulation. Therefore, wave breaking should be considered in SAR wave retrieval using the approach proposed in this paper under extreme sea states, such as typhoons and hurricanes.
Publisher
Taylor & Francis,National Satellite Ocean Application Service,Ministry of Natural Resources,Beijing,China%College of Marine Sciences,Shanghai Ocean University,Shanghai,China%National Satellite Ocean Application Service,Ministry of Natural Resources,Beijing,China,College of Marine Sciences,Shanghai Ocean University,Shanghai,China,Taylor & Francis Group