海底管道
钻探
鉴定(生物学)
卫星
化石燃料
遥感
石油工程
自动识别系统
石油钻井
数据源
资源(消歧)
环境科学
计算机科学
地质学
实时计算
海洋学
工程类
数据库
机械工程
计算机网络
植物
航空航天工程
生物
废物管理
作者
Caihong Ma,LinLin Guan,Dacheng Wang
出处
期刊:2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)
日期:2021-07-01
标识
DOI:10.1109/icnisc54316.2021.00076
摘要
The ocean is rich in oil and natural gas. The struggle for maritime rights and interests is becoming increasingly fierce. High temporal and spatial dynamic monitoring of offshore oil and gas drilling platforms has becoming important for comprehensive understanding of regional resource exploitation and development. In this paper, multi-source remote sensing satellite data are applied to the identification of offshore oil and gas platforms. And, an intelligent identification model of offshore oil and gas drilling platforms based on multi-source data is proposed. Firstly, the target area of offshore oil and gas platforms were first identified by ‘Flint’ annual NPP-VIIRS night-time light data. Then, they were accurately identified by combining the characteristics of multi temporal Sentinel-1 data. Finally, they were verified by combining multi-source high-resolution remote sensing satellite data. In this paper, the model was applied on the eastern sea area of Vietnam. And 75 platforms were rightly detected.
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