Global offshore wind turbine dataset

被引:69
作者
Zhang, Ting [1 ]
Tian, Bo [1 ]
Sengupta, Dhritiraj [1 ]
Zhang, Lei [2 ]
Si, Yali [3 ]
机构
[1] East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai 200062, Peoples R China
[2] Tongji Univ, Dept Traff Informat & Control Engn, Shanghai 201804, Peoples R China
[3] Inst Environm Sci, NL-2333 CC Leiden, Netherlands
关键词
KENDALL TREND TEST; FARMS;
D O I
10.1038/s41597-021-00982-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Offshore wind farms are widely adopted by coastal countries to obtain clean and green energy; their environmental impact has gained an increasing amount of attention. Although offshore wind farm datasets are commercially available via energy industries, records of the exact spatial distribution of individual wind turbines and their construction trajectories are rather incomplete, especially at the global level. Here, we construct a global remote sensing-based offshore wind turbine (OWT) database derived from Sentinel-1 synthetic aperture radar (SAR) time-series images from 2015 to 2019. We developed a percentile-based yearly SAR image collection reduction and autoadaptive threshold algorithm in the Google Earth Engine platform to identify the spatiotemporal distribution of global OWTs. By 2019, 6,924 wind turbines were constructed in 14 coastal nations. An algorithm performance analysis and validation were performed, and the extraction accuracies exceeded 99% using an independent validation dataset. This dataset could further our understanding of the environmental impact of OWTs and support effective marine spatial planning for sustainable development.
引用
收藏
页数:12
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