Next Article in Journal
A Method to Improve High-Resolution Sea Ice Drift Retrievals in the Presence of Deformation Zones
Next Article in Special Issue
Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation
Previous Article in Journal
Intercalibration and Gaussian Process Modeling of Nighttime Lights Imagery for Measuring Urbanization Trends in Africa 2000–2013
Previous Article in Special Issue
GF-3 SAR Ocean Wind Retrieval: The First View and Preliminary Assessment

An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

Marine Science and Technology College, Zhejiang Ocean University, Zhoushan 316000, China
Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China
Global Science and Technology, National Oceanic and Atmospheric Administration (NOAA)-National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA
Author to whom correspondence should be addressed.
Academic Editors: Xiaofeng Yang, Ferdinando Nunziata and Alexis Mouche
Remote Sens. 2017, 9(7), 711;
Received: 17 April 2017 / Revised: 28 June 2017 / Accepted: 6 July 2017 / Published: 11 July 2017
(This article belongs to the Special Issue Ocean Remote Sensing with Synthetic Aperture Radar)
In this study, we proposed an empirical algorithm for significant wave height (SWH) retrieval from TerraSAR-X/TanDEM (TS-X/TD-X) X-band synthetic aperture radar (SAR) co-polarization (vertical-vertical (VV) and horizontal-horizontal (HH)) images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR) has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS) to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field at a 0.125° grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) buoys. It is found that the algorithm performs well with a SWH stander deviation (STD) of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6–7 m), we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information. View Full-Text
Keywords: SAR; significant wave height; co-polarization; TerraSAR-X/TanDEM-X SAR; significant wave height; co-polarization; TerraSAR-X/TanDEM-X
Show Figures

Graphical abstract

MDPI and ACS Style

Shao, W.; Wang, J.; Li, X.; Sun, J. An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery. Remote Sens. 2017, 9, 711.

AMA Style

Shao W, Wang J, Li X, Sun J. An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery. Remote Sensing. 2017; 9(7):711.

Chicago/Turabian Style

Shao, Weizeng, Jing Wang, Xiaofeng Li, and Jian Sun. 2017. "An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery" Remote Sensing 9, no. 7: 711.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop