First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model
The HISEA-1 synthetic aperture radar (SAR) minisatellite has been orbiting for over two years since its launch in 2020, acquiring numerous high-resolution images independent of weather and daylight. A typical and important application is the observation of ocean waves, essential ocean dynamical phen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/14/3486 |
| _version_ | 1797587582416060416 |
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| author | Haiyang Sun Xupu Geng Lingsheng Meng Xiao-Hai Yan |
| author_facet | Haiyang Sun Xupu Geng Lingsheng Meng Xiao-Hai Yan |
| author_sort | Haiyang Sun |
| collection | DOAJ |
| description | The HISEA-1 synthetic aperture radar (SAR) minisatellite has been orbiting for over two years since its launch in 2020, acquiring numerous high-resolution images independent of weather and daylight. A typical and important application is the observation of ocean waves, essential ocean dynamical phenomena. Here, we proposed a new semi-automatic empirical method to retrieve ocean wave parameters from HISEA-1 images. We first applied some automated processing methods to remove non-wave information and artifacts, which largely improves the efficiency and robustness. Then, we developed an empirical model to retrieve significant wave height (SWH) by considering the dependence of SWH on azimuth cut-off, wind speed, and information extracted from the cross-spectrum. Comparisons with the Wavewatch III (WW3) data show that the performance of the proposed model significantly improved compared to the previous semi-empirical model; the root mean square error, correlation, and scattering index are 0.45 m (0.63 m), 0.87 (0.75), and 18% (26%), respectively. Our results are also consistent well with those from the altimeter measurements. Further case studies show that this new ocean wave model is reliable even under typhoon conditions. This work first provides accurate ocean-wave products from HISEA-1 SAR data and demonstrates its ability to perform high-resolution observation of coasts and oceans. |
| first_indexed | 2024-03-11T00:41:57Z |
| format | Article |
| id | doaj.art-54df448aa9494b3ea22558abbd04d46d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T00:41:57Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-54df448aa9494b3ea22558abbd04d46d2023-11-18T21:11:27ZengMDPI AGRemote Sensing2072-42922023-07-011514348610.3390/rs15143486First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical ModelHaiyang Sun0Xupu Geng1Lingsheng Meng2Xiao-Hai Yan3State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361005, ChinaState Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361005, ChinaCollege of the Environment and Ecology, Xiamen University, Xiamen 361005, ChinaJoint Center for Remote Sensing, University of Delaware-Xiamen University, Xiamen 361002, ChinaThe HISEA-1 synthetic aperture radar (SAR) minisatellite has been orbiting for over two years since its launch in 2020, acquiring numerous high-resolution images independent of weather and daylight. A typical and important application is the observation of ocean waves, essential ocean dynamical phenomena. Here, we proposed a new semi-automatic empirical method to retrieve ocean wave parameters from HISEA-1 images. We first applied some automated processing methods to remove non-wave information and artifacts, which largely improves the efficiency and robustness. Then, we developed an empirical model to retrieve significant wave height (SWH) by considering the dependence of SWH on azimuth cut-off, wind speed, and information extracted from the cross-spectrum. Comparisons with the Wavewatch III (WW3) data show that the performance of the proposed model significantly improved compared to the previous semi-empirical model; the root mean square error, correlation, and scattering index are 0.45 m (0.63 m), 0.87 (0.75), and 18% (26%), respectively. Our results are also consistent well with those from the altimeter measurements. Further case studies show that this new ocean wave model is reliable even under typhoon conditions. This work first provides accurate ocean-wave products from HISEA-1 SAR data and demonstrates its ability to perform high-resolution observation of coasts and oceans.https://www.mdpi.com/2072-4292/15/14/3486HISEA-1synthetic aperture radar (SAR)significant wave height (SWH)ocean waves |
| spellingShingle | Haiyang Sun Xupu Geng Lingsheng Meng Xiao-Hai Yan First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model Remote Sensing HISEA-1 synthetic aperture radar (SAR) significant wave height (SWH) ocean waves |
| title | First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model |
| title_full | First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model |
| title_fullStr | First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model |
| title_full_unstemmed | First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model |
| title_short | First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model |
| title_sort | first ocean wave retrieval from hisea 1 sar imagery through an improved semi automatic empirical model |
| topic | HISEA-1 synthetic aperture radar (SAR) significant wave height (SWH) ocean waves |
| url | https://www.mdpi.com/2072-4292/15/14/3486 |
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