Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm
With a widespread adoption of synthetic aperture radar (SAR) observations in Earth sciences, the volume of annual data updates has soared to petabyte scales. Consequently, the accurate retrieval and efficient storage of SAR data have become pressing concerns. The existing data searching method exhib...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10733747/ |
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| author | Kaiwen Yang Lei Zhang Jicang Wu Jinsong Qian |
| author_facet | Kaiwen Yang Lei Zhang Jicang Wu Jinsong Qian |
| author_sort | Kaiwen Yang |
| collection | DOAJ |
| description | With a widespread adoption of synthetic aperture radar (SAR) observations in Earth sciences, the volume of annual data updates has soared to petabyte scales. Consequently, the accurate retrieval and efficient storage of SAR data have become pressing concerns. The existing data searching method exhibits significant redundancy, leading to wasteful consumption of bandwidth and storage resources. Aiming to address this issue, we present here an optimized retrieval method grounded in a greedy algorithm, which can substantially reduce redundant data by approximately 20–65% while ensuring comprehensive data coverage over the areas of interest. By significantly minimizing redundant data, the proposed method markedly enhances data acquisition efficiency and conserves storage space. Validation experiments with Sentinel-1 data, employing various keyhole markup language scope files as inputs, affirm the effectiveness and reliability of the method. The application of the proposed method is expected to pave the way for efficient data management and fully automatic InSAR processing. |
| format | Article |
| id | doaj-art-19f2ab4a10b64babb35683f0b8a7644c |
| institution | DOAJ |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-19f2ab4a10b64babb35683f0b8a7644c2025-08-20T02:52:59ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352024-01-0117194781948610.1109/JSTARS.2024.348577110733747Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy AlgorithmKaiwen Yang0Lei Zhang1https://orcid.org/0000-0002-8152-2470Jicang Wu2Jinsong Qian3College of Surveying and Geo-Informatics, Tongji University, Shanghai, ChinaCollege of Surveying and Geo-Informatics, Tongji University, Shanghai, ChinaCollege of Surveying and Geo-Informatics, Tongji University, Shanghai, ChinaCollege of Transportation Engineering, Tongji University, Shanghai, ChinaWith a widespread adoption of synthetic aperture radar (SAR) observations in Earth sciences, the volume of annual data updates has soared to petabyte scales. Consequently, the accurate retrieval and efficient storage of SAR data have become pressing concerns. The existing data searching method exhibits significant redundancy, leading to wasteful consumption of bandwidth and storage resources. Aiming to address this issue, we present here an optimized retrieval method grounded in a greedy algorithm, which can substantially reduce redundant data by approximately 20–65% while ensuring comprehensive data coverage over the areas of interest. By significantly minimizing redundant data, the proposed method markedly enhances data acquisition efficiency and conserves storage space. Validation experiments with Sentinel-1 data, employing various keyhole markup language scope files as inputs, affirm the effectiveness and reliability of the method. The application of the proposed method is expected to pave the way for efficient data management and fully automatic InSAR processing.https://ieeexplore.ieee.org/document/10733747/Data retrievalgreedy algorithmsentinel-1synthetic aperture radar (SAR) |
| spellingShingle | Kaiwen Yang Lei Zhang Jicang Wu Jinsong Qian Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Data retrieval greedy algorithm sentinel-1 synthetic aperture radar (SAR) |
| title | Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm |
| title_full | Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm |
| title_fullStr | Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm |
| title_full_unstemmed | Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm |
| title_short | Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With Greedy Algorithm |
| title_sort | precise retrieval of sentinel 1 data by minimizing the redundancy with greedy algorithm |
| topic | Data retrieval greedy algorithm sentinel-1 synthetic aperture radar (SAR) |
| url | https://ieeexplore.ieee.org/document/10733747/ |
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