Retrieval of Sea Surface Wind Speeds from Gaofen-3 Full Polarimetric Data

TianYu, Zhang; Li, Xiao-Ming; Qian, Feng; Ren, Yongzheng; Shi, Yingni

doi:10.3390/rs11070813

Cited by 20 publications

(10 citation statements)

References 49 publications

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“…Unfortunately, in order to use the HH polarization in addition to VV polarization, the water HH polarization GMF should be available for the given frequency band as well. As appropriate operational water GMF for the HH polarization is currently not available at the C-band, a formula for the polarization ratio [36] can be used in that case until the appropriate water HH polarization C-band GMF is developed. As real azimuthal NRCS dependences are different at VV and HH polarizations, the polarization ratio should depend not only on the incidence angle but also on the azimuth angle.…”

Section: Methodsmentioning

confidence: 99%

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

et al. 2020

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Following the mission science plan of EPS/Metop-SG C-band scatterometer for 2023–2044, we consider the potential application of the sea ice/water discrimination method based on the minimum statistical distance of the measured normalized radar cross sections (NRCS) to the geophysical model functions (GMF) of the sea ice and water, respectively. The application of the method is considered for the classical spacecraft scatterometer geometry with three fixed fan-beam antennas and the hypothetical prospective scatterometer geometry with the five fixed fan-beam antennas. Joint vertical (VV) and horizontal (HH) transmit and receive polarization are considered for the spaceborne scatterometer geometries. We show explicitly that the hypothetical five fixed fan-beam antenna geometry combined with the dual VV and HH polarization for all antennas provides better estimates of the sea wind speed and direction as well as sea ice/water discrimination during single spacecraft pass. The sea ice/water discrimination algorithms developed for each scatterometer geometry and dual VV/HH polarization are presented. The obtained results can be used to optimize the design of new spaceborne scatterometers and will be beneficial to the forthcoming satellite missions.

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Section: Methodsmentioning

confidence: 99%

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

et al. 2020

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“…The basic parameters of the three patterns are shown in Table 1 [24]. ScanSAR modes of Gaofen-3 play an important role in the inversion of ocean parameters and ocean monitoring [25][26][27]. Take NSC as an example to illustrate the working mechanism of ScanSAR.…”

Section: Scalloping Modeling For Gf-3 Scansar Modementioning

confidence: 99%

An Improved Descalloping Method Combined With Imaging Parameters for GaoFen-3 ScanSAR

et al. 2020

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Due to the specific working mechanism of alternately transmitting and receiving signals between multiple adjacent swaths, scanning synthetic aperture radar (ScanSAR) will cause periodical wavelike modulation of the intensity image along azimuth direction, which is known as scalloping. Conventional descalloping methods are achieved by proper azimuth antenna pattern (AAP) correction and multi-looking techniques but are limited by the accuracy of Doppler centroid estimating and the thermal noise. Another type of method extracts and suppresses the scalloping texture on the image, but the scanning parameters of ScanSAR are insufficiently considered. The period of scalloping on the image is related to the period of switching between subswathes. While the harmonics can be calculated by the period of a periodic signal, an improved frequency filtering method combined with imaging parameters is proposed. The scalloping modulation model of ScanSAR combined with imaging parameters is constructed, and the harmonics of scalloping texture are accurately calculated and filtered. For the low signal to noise ratio (SNR) image, the antenna pattern is modified according to SNR to avoid scalloping caused by noise. For non-uniform scenes, scalloping suppression is achieved by using the scalloping features acquired by uniform scenes. To separate the non-uniform scenes from uniform scenes, we still use the characteristics of harmonics caused by scalloping. Our descalloping method achieves accurate suppression of scalloping without sea-land segmentation and ship mask and the residual scalloping is reduced from 1.0 to 0.3–0.5 dB. The residual scalloping and statistical characteristics of the image are analyzed to demonstrate the effectiveness of the proposed method.

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“…Flowchart of the RF model. Zhang et al (2019). Therefore, we thought that crosspolarization NRCS was useful for wind retrieval from the GF-3 SAR image.…”

Section: E Development Of Intelligent Wind Retrieval Algorithmmentioning

confidence: 99%

Intelligent Wind Retrieval from Chinese Gaofen-3 SAR Imagery in Quad Polarization

Shao

Zhu

Zhang

et al. 2019

Journal of Atmospheric and Oceanic Technology

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This study proposes the use of the artificial neural network for wind retrieval with Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) data. More than 10 000 images acquired in wave mode and quad-polarization strip map were collected over global seas throughout the 2-yr mission. The GF-3 operated in a quad-polarization channel—vertical–vertical (VV), vertical–horizontal (VH), horizontal–horizontal (HH), and horizontal–vertical (HV). These images were collocated with winds from the European Centre for Medium-Range Weather Forecasts at a 0.125° grid. The newly released wind retrieval algorithm for copolarization (VV and HH) SAR included CMOD7 and C-SARMOD2. We developed an algorithm based on an artificial neural network method using the SAR-measured normalized radar cross section at quad-polarization channels, herein named QPWIND_GF. Simulations using the QPWIND_GF showed that the correlation coefficient of wind speed was 0.94. We then validated the retrieval wind speeds against the measurements at a 0.25° grid from the Advanced Scatterometer. A comparison showed that the root-mean-square error (RMSE) of wind speed was 0.74 m s−1, which was better than the wind speed obtained using state-of-the-art methods—including, for example, CMOD7 (RMSE 0.88 m s−1) and C-SARMOD2 (RMSE 1.98 m s−1). The finding indicated that the accuracy of wind retrieval from GF-3 SAR images was significantly improved. Our work demonstrates the advanced feasibility of an artificial neural network method for SAR marine applications.

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Retrieval of Sea Surface Wind Speeds from Gaofen-3 Full Polarimetric Data

Cited by 20 publications

References 49 publications

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

An Improved Descalloping Method Combined With Imaging Parameters for GaoFen-3 ScanSAR

Intelligent Wind Retrieval from Chinese Gaofen-3 SAR Imagery in Quad Polarization

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