Technical Evaluation of Sentinel-1 IW Mode Cross-Pol Radar Backscattering from the Ocean Surface in Moderate Wind Condition

Huang, Lanqing; Liu, Bin; Li, Xiaofeng; Zhang, Zenghui; Yu, Wenxian

doi:10.3390/rs9080854

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Technical Evaluation of Sentinel-1 IW Mode Cross-Pol Radar Backscattering from the Ocean Surface in Moderate Wind Condition

2017
By Huang, Lanqing ; Liu, Bin ; Li, Xiaofeng ; ...
Source: Remote Sens. 2017, 9(8), 854

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Journal Title:

Remote Sensing
Personal Author:

Huang, Lanqing ; Liu, Bin ; Li, Xiaofeng ; Zhang, Zenghui ; Yu, Wenxian

Huang, Lanqing ; Liu, Bin ; Li, Xiaofeng ; Zhang, Zenghui ; Yu, Wenxian Less -
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research)

NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) Less -
Description:

The Sentinel-1 synthetic aperture radar (SAR) allows sufficient resources for cross-pol wind speed retrievals over the ocean. In this paper, we present technical evaluation on wind retrieval from both Sentinel-1A and Sentinel-1B IW cross-pol images. Algorithms are based on the existing theoretical and empirical ones derived from the RADARSAT-2 cross-pol data. First, to better understand the Sentinel-1 observed normalized radar cross section (NRCS) values under various environmental conditions, we constructed a dataset that integrates SAR images with wind field information from scatterometer measurements. There are 11,883 matchup data in the experimental dataset. We then calculated the systemic noise floor of Sentinel-1 IW mode, and presented its unique noise characteristics among different sub-bands. Based on the calculated NESZ measurements, the noise is removed for all matchup data. Empirical relationships among the noise free NRCS σ0VH , wind speed, wind direction, and radar incidence angle are analyzed for each sub-band, and a piecewise model is proposed. We showed that a larger correlation coefficient, r, is achieved by including both wind direction and incidence terms in the model. Validation against scatterometer measurements showed the suitability of the proposed model.
Keywords:

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Radar Remote Sensing Winds
Source:

Remote Sens. 2017, 9(8), 854
DOI:

https://doi.org/10.3390/rs9080854
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Journal Article
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CC BY
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Submitted
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urn:sha256:839a4df416ad65395be53f93d306d7ad37d78265513941b0af9f640608e94897
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https://repository.library.noaa.gov/view/noaa/43960/noaa_43960_DS1.pdf
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