Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Wang, He; Wang, Jing; Yang, Jianguo; Ren, Lin; Zhu, Jianrong; Yuan, Xiaojun; Xie, Changchun

doi:10.3390/rs10030363

Cited by 47 publications

(43 citation statements)

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“…Ocean wave retrieval algorithms include theoretical-based retrieval schemes, e.g., the "Max-Planck Institute" (MPI) [7][8][9], the Semi Parametric Retrieval Algorithm (SPRA) [10], the Partition Rescaling and Shift Algorithm (PARSA) [11], and the Parameterized First-guess Spectrum Method (PFSM) [12][13][14], as well as empirical models, e.g., CWAVE_ERS [15], CWAVE_ENVI [16], CWAVE_S1 [17], CSAR_WAVE [18,19], and QPCWAVE_GF3 [20]. All these algorithms have been developed to exploit SAR measurements collected at low and moderate sea states, due to the lack of SAR datasets collected at high sea state conditions.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

Shao

Yang

et al. 2018

Remote Sensing

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In this study, an empirical algorithm is proposed to retrieve significant wave height (SWH) from dual-polarization Sentinel-1 (S-1) synthetic aperture radar (SAR) imagery collected under cyclonic conditions. The retrieval scheme is based on the well-known CWAVE empirical function that is here updated to deal with multi-polarization S-1 SAR measurements collected using the interferometric wide (IW) and the Extra Wide-Swath (EW) imaging modes, under cyclonic conditions. First, a training dataset that consists of six S-1 SAR images collected under cyclonic conditions is exploited to both tune the retrieval function and to check the soundness of the retrievals against the co-located WAVEWATCH-III (WW3) numerical simulations. The comparison of simulation from the WW3 model and measurements from altimeter Jason-2 shows a 0.29m root mean square error (RMSE) of significant wave height (SWH). Then, a testing data-set that consists of two S-1 SAR images is exploited to provide a preliminary validation. The results, verified against both WW3 and European Centre for Medium-Range Weather Forecasts (ECMWF) data, show the soundness of the herein approach.

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Section: Introductionmentioning

confidence: 99%

An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

Shao

Yang

et al. 2018

Remote Sensing

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“…Ren et al [34] conducted a more detailed analysis of sea surface wind retrieval from GF-3 Quad-Polarization Stripmap (QPS) data, not only in the VV but also HH and HV polarizations. An empirical algorithm was proposed in [35] to derive significant wave height (SWH) from GF-3 wave mode data. In total, 12 coefficients of the empirical algorithm were tuned using the collocations of the GF-3 wave mode data with the WaveWatch III mode results.…”

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confidence: 99%

“…Remote Sens. 2018, 10, 1929 However, it seems that only cut-off information derived from the GF-3 data [36] may also yield a reasonable SWH compared with the rather complicated empirical algorithm in [35].After over two years of operation, GF-3 has acquired a large amount of global data; therefore, an overall assessment of its data quality and potential applications is essential. In this paper, we provide an overview of GF-3's capabilities in ocean and coastal observations, focusing on presenting representative cases over a few "super" test sites where similar studies have been conducted using other spaceborne SAR data, to evaluate the full polarimetry, high spatial resolution and wide-swath imaging capabilities of GF-3.…”

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Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

Zhang

Huang

et al. 2018

Remote Sensing

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Gaofen-3 (GF-3), the first Chinese spaceborne synthetic aperture radar (SAR) in C-band for civil applications, was launched on August 2016. Some studies have examined the use of GF-3 SAR data for ocean and coastal observations, but these studies generally focus on one particular application. As GF-3 has been in operation over two years, it is essential to evaluate its performance in ocean observation, a primary goal of the GF-3 launch. In this paper, we offer an overview demonstrating the capabilities of GF-3 SAR in ocean and coastal observations by presenting several representative cases, i.e., the monitoring of intertidal flats, offshore tidal turbulent wakes and oceanic internal waves, to highlight the GF-3's full polarimetry, high spatial resolution and wide-swath imaging advantages. Moreover, we also present a detailed analysis of the use of GF-3 quad-polarization data for sea surface wind retrievals and wave mode data for sea surface wave retrievals. The case studies and statistical analysis suggest that GF-3 has good ocean and coastal monitoring capabilities, though further improvements are possible, particularly in radiometric calibration and stable image quality.kilometers. Wide-swath or ScanSAR images generally have a spatial resolution of tens of meters and, more importantly, can map a large area of the open sea and coast, which makes them particularly suitable for studying meso-scale oceanic and atmospheric processes, e.g., by mapping the distribution of internal ocean waves [2], observing atmospheric solitons [3], estimating the wind speed of tropical cyclones [4], and measuring sea surface velocity [5].The year 2007 marks an important advance in the development of spaceborne SAR; two X-band spaceborne SAR, the TerraSAR-X (TSX) and Cosmo-SkyMed and the C-band SAR, Radarsat-2 (R2), were launched. Compared with previous spaceborne SAR missions, the new generation of SAR sensors has several advantages. One advantage is that the new generation can acquire images with a high spatial resolution of up to 1 m in spotlight mode [6][7][8]. This offers a unique opportunity to detect targets in the ocean and coast, e.g., for ship detection [9][10][11]. The other advantage is that these SAR sensors have polarimetric capabilities of acquiring data in different polarization combinations of VV, HH, VH and HV. These SAR polarimetric data are widely exploited for oil spill detection or classification [12][13][14], analysis of objects scattering or their classification in coastal intertidal flats [15][16][17], and sea ice detection and classification [18][19][20]. In addition to the general advantages of the aforementioned high spatial resolution and polarimetry, advanced SARs have constellation configuration design. The Cosmo-SkyMed, TSX/TanDEM-X (TDX) and Sentinel-1A/1B missions, as well as the forthcoming Radarsat Constellation Mission (RCM), all operate in constellations, which significantly reduces the temporal intervals of SAR data acquisition and therefore enhances the capture of dynamic sea surface information ...

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“…ice and slicks [2,47]. To screen out the Wave Mode images which are not affect by features due to slicks or ocean phenomenon, we use homogeneity check procedures proposed in [44] before experimental study. Wang et al [44] show that the Wave Mode normalized variance (cvar_vv) computed from VV-polarization images can be used as a standard for verifying image homogeneity.…”

Section: Introductionmentioning

confidence: 99%

Preliminary Analysis of Wind Retrieval Based on GF-3 Wave Mode Images

Wang¹,

Han²,

Yuan³

et al. 2018

Preprint

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In this paper, we analyze the measurements of the normalized radar cross-section(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, we verify the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. The Amazon rainforest experiment results show that the accuracy of obtained calibration constant meets the requirements. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it has an approximate cosine modulation with the wind direction when the wind speed is greater than 8m/s. The cross-polarized system noise floor is low enough to ignore it in wind retrieval. Furthermore, we also investigate the properties of the polarization ratio, denoted PR, and show that it is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σ_VV^0 retrieved from new PR models as well as σ_HH^0 is in good agreement with σ_VV^0 extracted from SAR images directly. And it is also shown that considering the azimuth angle can improve polarization conversion accuracy.

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Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Cited by 47 publications

References 45 publications

An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

Preliminary Analysis of Wind Retrieval Based on GF-3 Wave Mode Images

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