Article

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

Details

Citation

Zhu S, Shao W, Armando M, Shi J, Sun J, Yuan X, Hu J, Yang D & Zuo J (2020) Evaluation of Chinese Quad-polarization Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval. Canadian Journal of Remote Sensing, 44 (6), pp. 588-600. https://doi.org/10.1080/07038992.2019.1573136

Abstract
Our work describes the accuracy of Chinese quad-polarization Gaofen-3 (GF-3) synthetic aperture radar (SAR) wave mode data for wave retrieval and provides guidance for the operational applications of GF-3 SAR. In this study, we evaluated the accuracy of the SAR-derived significant wave height (SWH) from 10,514 GF-3 SAR images with visible wave streaks 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 were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field with 0.125° grids. The root mean square error (RMSE) of the SWH is 0.57 m, found using CSAR_WAVE2, and this RMSE value was less than the RMSE values for the analysis results achieved with the PFSM and Q-P algorithms. The statistical analysis also indicated that wind speed had little impact on the bias with increasing wind speed. However, the retrieval tended to overestimate when the SWH was smaller than 2.5 m and underestimate with an increasing SWH. This behavior provides a perspective of the improvement needed for the SWH retrieval algorithm using the GF-3 SAR acquired in wave mode.

Keywords
General Earth and Planetary Sciences

Journal
Canadian Journal of Remote Sensing: Volume 44, Issue 6

StatusPublished
FundersEuropean Space Agency
Publication date31/12/2020
Publication date online15/02/2019
Date accepted by journal15/01/2019
URLhttp://hdl.handle.net/1893/28850
PublisherInforma UK Limited
ISSN0703-8992
eISSN1712-7971

People (1)

People

Dr Armando Marino

Dr Armando Marino

Associate Professor, Biological and Environmental Sciences