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
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessFeature PaperArticle
Remote Sens. 2017, 9(7), 711;

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
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)
Full-Text   |   PDF [5775 KB, uploaded 11 July 2017]   |  


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

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Printed Edition Available!
A printed edition of this Special Issue is available here.

Share & Cite This Article

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.

Show more citation formats Show less citations formats

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

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top