Remote Sensing (Oct 2022)

Evaluation of Multi-Incidence Angle Polarimetric Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval

  • Chenqing Fan,
  • Tianran Song,
  • Qiushuang Yan,
  • Junmin Meng,
  • Yuqi Wu,
  • Jie Zhang

DOI
https://doi.org/10.3390/rs14215480
Journal volume & issue
Vol. 14, no. 21
p. 5480

Abstract

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Significant wave height (SWH) is one of the most important descriptors for ocean wave fields. The polynomial regression (PolR) and Gaussian process regression (GPR) models are implemented to explore the effects of polarization and incidence angles on the SWH estimation from multi-incidence angle quad-polarization Gaofen-3 SAR wave mode data, based on the collocated data set of approximately 12,000 Gaofen-3 wave mode imagettes, matched with SWH from the fifth generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The results show that the model performance improves, as long as polarimetry information increases. The hybrid polarizations perform stronger than the co-polarizations or cross-polarizations alone, and they show better performance over the low to high seas. The lower incidence angles are more favorable for SAR SWH inversion. It is superior to introduce incidence angle in piecewise way, rather than to include it as an independent variable in the models. Then, the final PolR and GPR models, with the superior input scheme that includes the quad-polarized features and introduces the incidence angle in piecewise way, are assessed independently through a comparison with observations from altimeter and buoys. The accuracies of our SWH estimates are comparable or even higher than other published results. The GPR model outperforms the PolR model, due to the superiority of the added nonlinearity of GPR.

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