Validation of significant wave height retrieval from co-polarization Chinese Gaofen-3 SAR imagery using an improved algorithm

Yang

et al. 2018

Remote Sensing

Self Cite

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.

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yang

et al. 2018

Remote Sensing

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“…It can be seen from our recent study (Sheng et al 2018) that the RMSE of the SWH is about 0.52m for co-polarization GF-3 SAR imaging mode acquired in QPS-I/II when retrieval results are compared with the measurements from altimeter Jason-2. It was also found that CSAR_WAVE2 has a better performance of wave retrieval for GF-3 SAR than the analysis results achieved when using the other empirical algorithms proposed in Wang et al (2012), Ren et al (2015) and Grieco et al (2016).…”

Section: Csar_wave2mentioning

confidence: 97%

“…In addition, several recent studies have developed algorithms to retrieve SWH through the cutoff wavelength at C-band for R-2 (Ren et al 2015), S-1 SAR (Shao et al 2016;Grieco et al 2016;Stopa and Mouche, 2017). In our recent study, an empirical algorithm is exploited for GF-3 SAR in co-polarization, named CSAR_WAVE2 (Sheng et al 2018). CSAR_WAVE2 employs the basic formulation of the CWAVE model, in which the coefficients are tuned through 1523 GF-3 SAR QPS-I/II mode images with collocated European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis SWH data at 0.125 grids.…”

mentioning

confidence: 99%

Evaluation of Chinese Quad-polarization Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval

Zhu

Canadian Journal of Remote Sensing

Marino

et al. 2018

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Our work describes the accuracy of the Chinese quad-polarization Gaofen-3 (GF-3) synthetic aperture radar (SAR) wave mode data for wave retrieval and provides guidance for operational applications of GF-3 SAR. In this study, we have evaluated the accuracy of SAR-derived significant wave height (SWH) from 10514 GF-3 SAR images with visible wave streak acquired in wave mode by using the existing wave retrieval algorithms, e.g., the theoretical-based algorithm parameterized first-guess spectrum method (PFSM), the empirical algorithm CSAR_WAVE2 for VV-polarization, and the algorithm for quad-polarization (Q-P). The retrieved SWHs are compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field at 0.125° grids. The root mean square error (RMSE) of SWH is 0.57m by using CSAR_WAVE2 is achieved, which is less than the analysis results achieved by using algorithm PFSM and Q-P. The statistical analysis also indicates that wind speed has little impact on bias with increasing wind speed.However, the retrieval tends to overestimate when SWH is smaller than 2.5m and

“…Figure 1 shows the footprints of available GF-3 images for this study. For calculating the NRCS from VV- and HH-polarization GF-3 SAR intensity images, the digital number (DN) is converted into NRCS following Sheng et al (2018):…”

Section: Datasetmentioning

confidence: 99%

Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

European Journal of Remote Sensing

Nunziata

Zhang

et al. 2021

Self Cite

In this study, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C-band Gaofen-3 (GF-3) SAR. More than 10,000 Vertical-Vertical (VV) and Horizontal-Horizontal (HH) polarization GF-3 images acquired in quad-polarization stripmap (QPS) and wave (WV) modes have been collected during the last three years, in which wind patterns are observed over open seas with incidence angles ranging from 18° to 52°. These images, collocated with wind vectors from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis at 0.125° resolution, are used to re-tune the C-SARMOD2 algorithm to specialize it for the GF-3 SAR (CSARMOD-GF). In particular, the CSARMOD-GF performs differently from the C-SARMOD2 at low-to-moderate incidence angles smaller than about 34°. Comparisons with wind speed data from the Advanced Scatterometer (ASCAT), Chinese Haiyang-2B (HY-2B) and buoys from the National Data Buoy Center (NDBC) show that the root-mean-square error (RMSE) of the retrieved wind speed is approximately 1.8 m/s. Additionally, the CSARMOD-GF algorithm outperforms three state-of-the-art methods -C-SARMOD, C-SARMOD2, and CMOD7 -that, when applied to GF-3 SAR imagery, generating a RMSE of approximately 2.0-2.4 m/s.