Improving SAR wind retrieval through automatic anomalous pixel detection
Satellite observations are increasingly in demand and valuable for monitoring the ocean and coastal winds in near-real-time and analyzing the data historically. However, soared up human activities, man-made constructions, and marine traffics negatively interfere and affect the reliability of observa...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-08-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223002686 |
| _version_ | 1797737970689638400 |
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| author | Abdalmenem Owda Jørgen Dall Merete Badger Dalibor Cavar |
| author_facet | Abdalmenem Owda Jørgen Dall Merete Badger Dalibor Cavar |
| author_sort | Abdalmenem Owda |
| collection | DOAJ |
| description | Satellite observations are increasingly in demand and valuable for monitoring the ocean and coastal winds in near-real-time and analyzing the data historically. However, soared up human activities, man-made constructions, and marine traffics negatively interfere and affect the reliability of observations and raise concerns about the trustworthiness of using satellite winds for many applications, such as offshore wind energy, even though Sentinel synthetic aperture radar (SAR) data is freely and easily accessible.In this paper, we presented a novel methodological framework for localization and suppression of anomalous pixels (APs), which deteriorate the confidence and accuracy of the retrieved SAR wind speeds. The backbone of the implementation relied on the constant false alarm rate (CFAR) algorithm, one of the automatic target recognition algorithms. We used a large dataset of SAR subscenes to model different sea clutter conditions after removing the potential targets. We selected the suitable distribution model that maintains a constant probability of false alarm (pfa) for the entire SAR scene. The proper pfa was optimized in various SAR scenes ranging from scenes with a considerable number of APs, such as ships and wind park clusters, to scenes with no visible APs under different wind speed conditions. The pfa optimization process prevented real wind pixels from being misidentified as APs.Applying CFAR to the logarithmic scale of raw digital numbers (log-DNs) domain with a pfa of about 3.17 × 10-5, we extracted SAR wind speeds around each ocean buoy before and after CFAR process, comparing them with their corresponding in situ wind measurements. This led to significant improvement in the quality and accuracy of SAR wind data retrieval, especially in regions with numerous man-made constructions and high marine traffics. We tested and validated our approach in the North Sea and two regions along the eastern coast of the U.S. The enclosed region, serving as a marine route for harbors in Delaware Bay, showed a substantial improvement in RMSE and BIAS after applying our approach, reducing RMSE from 2.4 m/s to 1.6 m/s and the BIAS from −1.5 m/s to −0.3 m/s. The open ocean region demonstrated stable RMSE and BIAS, indicating preservation of real wind data, as only APs affecting SAR wind speed were considered during the process. |
| first_indexed | 2024-03-12T13:37:09Z |
| format | Article |
| id | doaj.art-37a8a3ea6d4548e5a8a5713b4b93f1f6 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-12T13:37:09Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-37a8a3ea6d4548e5a8a5713b4b93f1f62023-08-24T04:34:21ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-08-01122103444Improving SAR wind retrieval through automatic anomalous pixel detectionAbdalmenem Owda0Jørgen Dall1Merete Badger2Dalibor Cavar3Technical University of Denmark, DTU Wind and Energy Systems, Frederiksborgvej 399, 4000 Roskilde, Denmark; Corresponding author.Technical University of Denmark, National Space Institute, Ørsteds Plads, building 348, Kgs. Lyngby, DenmarkTechnical University of Denmark, DTU Wind and Energy Systems, Frederiksborgvej 399, 4000 Roskilde, DenmarkTechnical University of Denmark, DTU Wind and Energy Systems, Frederiksborgvej 399, 4000 Roskilde, DenmarkSatellite observations are increasingly in demand and valuable for monitoring the ocean and coastal winds in near-real-time and analyzing the data historically. However, soared up human activities, man-made constructions, and marine traffics negatively interfere and affect the reliability of observations and raise concerns about the trustworthiness of using satellite winds for many applications, such as offshore wind energy, even though Sentinel synthetic aperture radar (SAR) data is freely and easily accessible.In this paper, we presented a novel methodological framework for localization and suppression of anomalous pixels (APs), which deteriorate the confidence and accuracy of the retrieved SAR wind speeds. The backbone of the implementation relied on the constant false alarm rate (CFAR) algorithm, one of the automatic target recognition algorithms. We used a large dataset of SAR subscenes to model different sea clutter conditions after removing the potential targets. We selected the suitable distribution model that maintains a constant probability of false alarm (pfa) for the entire SAR scene. The proper pfa was optimized in various SAR scenes ranging from scenes with a considerable number of APs, such as ships and wind park clusters, to scenes with no visible APs under different wind speed conditions. The pfa optimization process prevented real wind pixels from being misidentified as APs.Applying CFAR to the logarithmic scale of raw digital numbers (log-DNs) domain with a pfa of about 3.17 × 10-5, we extracted SAR wind speeds around each ocean buoy before and after CFAR process, comparing them with their corresponding in situ wind measurements. This led to significant improvement in the quality and accuracy of SAR wind data retrieval, especially in regions with numerous man-made constructions and high marine traffics. We tested and validated our approach in the North Sea and two regions along the eastern coast of the U.S. The enclosed region, serving as a marine route for harbors in Delaware Bay, showed a substantial improvement in RMSE and BIAS after applying our approach, reducing RMSE from 2.4 m/s to 1.6 m/s and the BIAS from −1.5 m/s to −0.3 m/s. The open ocean region demonstrated stable RMSE and BIAS, indicating preservation of real wind data, as only APs affecting SAR wind speed were considered during the process.http://www.sciencedirect.com/science/article/pii/S1569843223002686SARCFARAnomalous pixelSentinel-1Offshore wind farmCoastal environment |
| spellingShingle | Abdalmenem Owda Jørgen Dall Merete Badger Dalibor Cavar Improving SAR wind retrieval through automatic anomalous pixel detection International Journal of Applied Earth Observations and Geoinformation SAR CFAR Anomalous pixel Sentinel-1 Offshore wind farm Coastal environment |
| title | Improving SAR wind retrieval through automatic anomalous pixel detection |
| title_full | Improving SAR wind retrieval through automatic anomalous pixel detection |
| title_fullStr | Improving SAR wind retrieval through automatic anomalous pixel detection |
| title_full_unstemmed | Improving SAR wind retrieval through automatic anomalous pixel detection |
| title_short | Improving SAR wind retrieval through automatic anomalous pixel detection |
| title_sort | improving sar wind retrieval through automatic anomalous pixel detection |
| topic | SAR CFAR Anomalous pixel Sentinel-1 Offshore wind farm Coastal environment |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223002686 |
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