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A Neural Network Method for Retrieving Sea Surface Wind Speed for C-Band SAR

Peng Yu, Wenxiang Xu, Xiaojing Zhong, Johnny A. Johannessen, Xiao-Hai Yan, Xupu Geng, Yuanrong He, Wenfang Lu
2022 Remote Sensing  
Based on the Ocean Projection and Extension neural Network (OPEN) method, a novel approach is proposed to retrieve sea surface wind speed for C-band synthetic aperture radar (SAR).  ...  It is anticipated that the use of high-resolution SAR data together with the new wind speed retrieval method can provide continuous and accurate ocean wind products in the future.  ...  Acknowledgments: The authors would like to thank the ESA, EUMETSAT, and NOAA for the provision of Sentinel-1 SAR, ASCAT, and NDBC buoy data.  ... 
doi:10.3390/rs14092269 fatcat:osyd2hl2lffabcgu5rmfc4gvyi

Retrieval of Sea Surface Wind Speed from Spaceborne SAR over the Arctic Marginal Ice Zone with a Neural Network

Xiao-Ming Li, Tingting Qin, Ke Wu
2020 Remote Sensing  
In this paper, we presented a method for retrieving sea surface wind speed (SSWS) from Sentinel-1 synthetic aperture radar (SAR) horizontal-horizontal (HH) polarization data in extra-wide (EW) swath mode  ...  Verification of the neural network based on the testing dataset yields a bias of 0.23 m/s and a root mean square error (RMSE) of 1.25 m/s compared to the scatterometer wind data for wind speeds less than  ...  Introduction The retrieval of sea surface wind by spaceborne synthetic aperture radar (SAR) has been studied for a few decades.  ... 
doi:10.3390/rs12203291 fatcat:zlcijuiyabhztcnc5mz7j77ts4

Intelligent Wind Retrieval from Chinese Gaofen-3 SAR Imagery in Quad-Polarization

Weizeng Shao, Shuai Zhu, Xiaopeng Zhang, Shuiping Gou, Changzhe Jiao, Xinzhe Yuan, Liangbo Zhao
2019 Journal of Atmospheric and Oceanic Technology  
This study proposes the use of the artificial neural network for wind retrieval with Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) data.  ...  Our work demonstrates the advanced feasibility of an artificial neural network method for SAR marine applications.  ...  As a nonlinear regression algorithm, GBDT is also suitable for sea surface wind speed retrieval.  ... 
doi:10.1175/jtech-d-19-0048.1 fatcat:l5g7gmmlbrbbrnc4jzd3eytkou

Global wind speed retrieval from sar

J. Horstmann, H. Schiller, J. Schulz-Stellenfleth, S. Lehner
2003 IEEE Transactions on Geoscience and Remote Sensing  
The second approach is based on neural networks (NNs), which allow the retrieval of wind speeds from uncalibrated SAR imagettes.  ...  In this paper, two methods for retrieving wind speeds from SAR imagettes are presented and validated, showing the applicability of ENVISAT alike SAR wave mode data for global ocean wind retrieval.  ...  ACKNOWLEDGMENT The ERS-2 SAR image mode raw data were kindly provided by the European Space Agency.  ... 
doi:10.1109/tgrs.2003.814658 fatcat:grbyjpz3jve7ni35o2tak3vh3m

Approaches for Joint Retrieval of Wind Speed and Significant Wave Height and Further Improvement for Tiangong-2 Interferometric Imaging Radar Altimeter

Guo Li, Yunhua Zhang, Xiao Dong
2022 Remote Sensing  
The proposed method can achieve joint retrieval of wind speed and SWH accurately, which complements the existing wind speed and SWH retrieval methods for InIRA.  ...  Based on the retrieved SWH, two enhanced wind speed retrieval models are developed for high sea states and low sea states, respectively.  ...  The authors would also like to thank the American National Data Buoy Center for providing the buoy data and the NOAA's National Centers for Environmental Information for providing the ETOPO1 data.  ... 
doi:10.3390/rs14081930 fatcat:ff425sk3sfhmxgp455vh2ygely

Retrieval and Assessment of Significant Wave Height from CYGNSS Mission Using Neural Network

Feng Wang, Dongkai Yang, Lei Yang
2022 Remote Sensing  
Without the auxiliary of the wind speed, the SWH retrieved using the trained neural network exhibits a bias and an RMSE of −0.13 and 0.59 m with respect to ECMWF data.  ...  Due to the complex scattering of electromagnetic waves on the rough sea surface, the neural network approach is adopted to develop an algorithm to derive significant wave height (SWH) from CYGNSS data.  ...  Acknowledgments: We would like to thank the National Aeronautics and Space Administration (NASA) and the European Center for Medium-range Weather Forecasts (ECMWF) for providing the CYGNSS measurement  ... 
doi:10.3390/rs14153666 fatcat:b7sfg3gj6fddhgjgxpkh22li4q

Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

He Wang, Jingsong Yang, Jianhua Zhu, Lin Ren, Yahao Liu, Weiwei Li, Chuntao Chen
2021 Remote Sensing  
Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.  ...  Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge.  ...  Acknowledgments: The authors are grateful for two anonymous reviewers for giving constructive comments and suggestions to help improve this paper.  ... 
doi:10.3390/rs13020195 fatcat:ebrklwnxcfgb3ilytr3hwqqxa4

Table of contents

2021 IEEE Geoscience and Remote Sensing Letters  
Jiao 1585 A Curvature-Based Saliency Method for Ship Detection in SAR Images ... M. Yang, C. Guo, H. Zhong, and H.  ...  He 1550 Wind Speed Extraction Based on High Frequency Radar Retrieved Wind-Driven Current ................................ ..............................................................................  ... 
doi:10.1109/lgrs.2021.3105736 fatcat:gb4k7oxfkzb7lflayjkcf4uvtm

Oil-Spill Pollution Remote Sensing by Synthetic Aperture Radar [chapter]

Yuanzhi Zhang, Yu Li, Hui Lin
2014 Advanced Geoscience Remote Sensing  
It is worth noting that the detectability of oil-spill by SAR relies closely on the wind speed above sea surface: if the sea surface wind speed is too slow, sea wave cannot be well developed and if it  ...  Neural networks have been largely investigated and recognized as a robust tool for classification.  ... 
doi:10.5772/57477 fatcat:nfgxxxsehfatlclxrqj4juuza4

Rain Rate Estimation with SAR using NEXRAD measurements with Convolutional Neural Networks [article]

Aurélien Colin
2022 arXiv   pre-print
For a number of decades, C-band SAR imagery such a such as Sentinel-1 imagery has been known to exhibit rainfall signatures over the sea surface.  ...  Compared to current methods that rely on Koch filters to draw binary rainfall maps, these multi-threshold learning-based models can provide rainfall estimation for higher wind speeds and thus may be of  ...  We thank Alexis Mouche (Laboratoire d'Océanographie Physique et Spatiale, Ifremer) for the access to colocalizations between NEXRAD and Sentinel-1.  ... 
arXiv:2207.07333v1 fatcat:g764bu625nhgjfgbjlxmsplrp4

Application of a new algorithm using Doppler information to retrieve complex wind fields over the Black Sea from ENVISAT SAR images

Werner Alpers, Alexis Mouche, Jochen Horstmann, Andrei Yu. Ivanov, Vladyslav S. Barabanov
2015 International Journal of Remote Sensing  
Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean.  ...  Recently, a new wind retrieval algorithm has been proposed, which also includes the Doppler shift induced by motions of the sea surface.  ...  Acknowledgements We thank NERSC in Bergen, Norway, for providing the wind fields depicted in Figures 2(a) , 6(a), and 12(a) from their SAR archive, which were calculated from ASAR images using CMOD4 and  ... 
doi:10.1080/01431161.2014.999169 fatcat:uvefbm5ux5fgrpdpzzrfnzsmsa

Multi-modal deep learning models for ocean wind speed estimation

Clémentin Boittiaux, Paul Nguyen Hong Duc, Nicolas Longépé, Sara Pensieri, Roberto Bozzano, Dorian Cazau
2020 European Conference on Principles of Data Mining and Knowledge Discovery  
Because it depends on multiple atmospheric and oceanographic variables interacting with each other at the sea surface, accurately forecasting offshore surface wind speed is challenging for oceanographers  ...  Qualitative and quantitative results obtained demonstrate that SAR images are able to refine the estimation of UPA for low wind speeds.  ...  The RMSE of the wind speed generated by C-band SAR image is in the order of 1.5 m/s.  ... 
dblp:conf/pkdd/BoittiauxDLPBC20 fatcat:bjap3gkmwrb33kfybgg2i3ncse

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y.  ...  , see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang, B., Dong, X., and Li, Y., Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite; TGRS Sept.  ...  ., +, TGRS Sept. 2019 6986-6995 A Novel Azimuth Cutoff Implementation to Retrieve Sea Surface Wind Speed From SAR Imagery.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Past, Present and Future Marine Microwave Satellite Missions in China

Mingsen Lin, Yongjun Jia
2022 Remote Sensing  
A long-term plan has now been formulated for the development of Chinese ocean satellites, as well as the construction of a constellation of ocean dynamic environmental and ocean surveillance satellites  ...  These will gradually form China's ocean monitoring network from space, thereby playing important roles in future ocean resource and environmental monitoring, marine disaster prevention and reduction, and  ...  In addition, the authors would like to thank Zhixiong Wang for his assistance in the data processing. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14061330 fatcat:t273nxqkundyjk3m256vbyuvwi

Direction-of-Arrival Estimation over Sea Surface from Radar Scattering Based on Convolutional Neural Network

Xiuyi Zhao, Ying Yang, Kun-Shan Chen
2021 Remote Sensing  
This paper proposes a novel DOA estimation approach for SAR systems using the simulated radar measurement of the sea surface at different operating frequencies and wind speeds.  ...  Results demonstrate that the CNN can achieve a good performance in DOA estimation at a wide range of frequencies and sea wind speeds.  ...  Conclusions In this study, we present a novel method of two-dimensional DOA estimation for SAR systems based on sea surface scattering and convolutional neural networks.  ... 
doi:10.3390/rs13142681 fatcat:gk2zf3cp75eovm2w67y3hydjle
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