| 基于Sentinel-1A 影像的海上油气平台遥感识别方法———以渤海为例 |
| Remote Sensing Recognition Method of Offshore Oil and Gas Platforms Based on Sentinel-1A Image: A Case Study of Bohai Sea |
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| DOI： |
| 中文关键词: 影像识别 Sentinel-1A 海上油气平台 渤海 Matthew 极化增强 |
| 英文关键词:image recognition Sentinel-1A offshore oil and gas platforms Bohai Sea Matthew polarization enhancement |
| 基金项目:教育部人文社会科学重点研究基地重大项目（22JJD790028） |
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| 中文摘要: |
| 针对难以准确获取海上油气平台位置信息这一问题，本文提出了一种基于Sentinel-1A影像的海上油气平台快速识别方法。该方法先对水平发射水平接收（Vertical Transmit，Vertical Receive，VV）、水平发射垂直接收（Vertical Transmit，Horizontal Receive，VH） 极化数据进行处理，而后运用Matthew 极化增强算法分离油气平台和船舶、高亮海水等，最后通过陆地掩膜、风力涡轮机去除等操作完成目标点位的获取。利用谷歌地球引擎（Google Earth Engine，GEE）对渤海海域2023 年9—11 月的28 景Sentinel-1A 数据进行平台提取，结果表明：渤海油气平台多集中于渤海湾和莱州湾；提取正确率为92.58%，检测率为96.34%；该方法可操作性强、精准度高，能为广域的海洋资源检测提供技术支持。 |
| 英文摘要: |
| To address the challenge of accurate location acquisition of offshore oil and gas platforms, this paper proposed a speedy identification method based on Sentinel-1A imagery. The method begins with processing the Vertical Transmit, Vertical Receive (VV) and Vertical Transmit, Horizontal Receive (VH) polarization data, and the application of the Matthew polarization enhancement algorithm to separate oil and gas platforms, ships and bright seawater follows. Finally, the target spots are achieved through operations of land mask and wind turbine removal. Using the Google Earth Engine (GEE) platform to extract 28 Sentinel-1A datasets from September to November in 2023 in the Bohai Sea, the results indicate that oil and gas platforms in the Bohai Sea mainly concentrate in Bohai Bay and Laizhou Bay. The extraction accuracy rate is 92.58%, and the detection rate is 96.34%. This method demonstrates strong operability and high accuracy, offering technical support for wide-area marine resource detection. |
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