The internal wave extraction from composing sea surface using SAR image

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477) ◽

10.1109/igarss.2003.1294547 ◽

2004 ◽

Author(s):

Dong Qing ◽

Guo Huadong ◽

Han Chunming

Keyword(s):

Internal Wave ◽

Sea Surface ◽

Sar Image

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An Automatic Data-Driven Method for SAR Image Segmentation in Sea Surface Analysis

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2017.2769710 ◽

2018 ◽

pp. 1-14 ◽

Cited By ~ 4

Author(s):

Laura Gemme ◽

Silvana G. Dellepiane

Keyword(s):

Image Segmentation ◽

Surface Analysis ◽

Sea Surface ◽

Data Driven ◽

Sar Image ◽

Automatic Data ◽

Sar Image Segmentation

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Water temperature at the sea surface. (V) Influences of the internal wave

Deep Sea Research and Oceanographic Abstracts ◽

10.1016/0011-7471(64)90252-9 ◽

1964 ◽

Vol 11 (2) ◽

pp. 321-322

Keyword(s):

Internal Wave ◽

Water Temperature ◽

Sea Surface

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Study of electromagnetic composite scattering from a ship-generated internal wave wake and its underlying sea surface

Waves in Random and Complex Media ◽

10.1080/17455030.2015.1066044 ◽

2015 ◽

Vol 25 (4) ◽

pp. 628-643 ◽

Cited By ~ 1

Author(s):

Ning Li ◽

Min Zhang ◽

Ding Nie ◽

Rong-Qing Sun

Keyword(s):

Internal Wave ◽

Sea Surface

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Comparison analysis of Ku-band SLAR sea surface images at VV and HH polarizations obtained during the joint US/Russia Internal Wave Remote Sensing Experiment

Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.1994.399247 ◽

2005 ◽

Cited By ~ 3

Author(s):

V.S. Etkin ◽

Yu.G. Trokhimovski ◽

V.V. Yakovlev ◽

R.F. Gasparovic

Keyword(s):

Remote Sensing ◽

Internal Wave ◽

Sea Surface ◽

Comparison Analysis ◽

Ku Band ◽

Surface Images

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Automatic Feature Detection of Ocean Internal Wave SAR Image Based on Hierarchical Clustering

Computer Science and Application ◽

10.12677/csa.2019.96126 ◽

2019 ◽

Vol 09 (06) ◽

pp. 1118-1125

Author(s):

素芹许

Keyword(s):

Internal Wave ◽

Hierarchical Clustering ◽

Feature Detection ◽

Sar Image

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An Accelerated Algorithm Based on GO-PO/PTD and CWMFSM for EM Scattering From the Ship Over a Sea Surface and SAR Image Formation

IEEE Transactions on Antennas and Propagation ◽

10.1109/tap.2019.2963241 ◽

2020 ◽

Vol 68 (5) ◽

pp. 3934-3944 ◽

Cited By ~ 1

Author(s):

Chun-Lei Dong ◽

Li-Xin Guo ◽

Xiao Meng

Keyword(s):

Image Formation ◽

Sea Surface ◽

Sar Image ◽

Em Scattering

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Study on extracting and verifying internal wave parameter of SAR image

10.1117/12.2194768 ◽

2015 ◽

Cited By ~ 2

Author(s):

Juan Wang ◽

Jingsong Yang ◽

Junde Li ◽

Lin Ren ◽

Gang Zheng

Keyword(s):

Internal Wave ◽

Wave Parameter ◽

Sar Image

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Internal wave parameters retrieval from SAR image: based on EMD filter and parameterized buoyancy frequency

2007 1st Asian and Pacific Conference on Synthetic Aperture Radar ◽

10.1109/apsar.2007.4418723 ◽

2007 ◽

Author(s):

Fei Li ◽

Jinsong Chong ◽

Yue Ouyang

Keyword(s):

Internal Wave ◽

Buoyancy Frequency ◽

Sar Image ◽

Wave Parameters

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A method for sea surface wind field retrieval from SAR image mode data

Journal of Ocean University of China ◽

10.1007/s11802-014-1999-5 ◽

2014 ◽

Vol 13 (2) ◽

pp. 198-204 ◽

Cited By ~ 11

Author(s):

Weizeng Shao ◽

Jian Sun ◽

Changlong Guan ◽

Zhanfeng Sun

Keyword(s):

Wind Field ◽

Surface Wind ◽

Sea Surface ◽

Sar Image ◽

Sea Surface Wind ◽

Surface Wind Field

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One Operational Method for Offshore Wind Speeds Retrieval from SAR Image

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1092-1093.47 ◽

2015 ◽

Vol 1092-1093 ◽

pp. 47-51

Author(s):

Xu Yan Fan ◽

Peng Chen ◽

Kai Guo Fan ◽

Zhong Tang

Keyword(s):

Wind Energy ◽

Surface Wind ◽

Sea Surface ◽

Offshore Wind ◽

Sar Image ◽

Operational Method ◽

Wind Speeds ◽

Sea Surface Wind ◽

Business Application ◽

Mean Square Errors

The high resolution offshore wind speeds retrieval from SAR image is of great signification in the field of offshore wind energy estimation. In this paper, one operational method for offshore wind speeds retrieval from SAR image is conducted. Taking one scene ENVISAT ASAR image as a case study, the offshore wind speeds is operational retrieved combing with the NCEP/QSCAT blended sea surface wind directions. The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds. The results show that they are in good agreement. The root mean square errors of wind speed are 1.9 m/s and 1.6 m/s respectively, which show that the operational method for offshore wind speeds retrieval from SAR is available and give the orientation of SAR offshore sea surface wind energy business application in the future.

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