Abstract
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.
Highlights
Background & SummaryOffshore wind farms, which comprise a cluster, or array, of wind turbines, is widely accepted as renewable sources of energy and effective ways to reduce greenhouse gas emissions and promote a net-zero carbon economy
Using the clean energy generated by offshore wind farms can help to achieve Intergovernmental Panel on Climate Change (IPCC) targets and meet the Sustainable Development Goals (SDGs) by regulating emissions and promoting developments in the renewable energy sector (Goal 13), ensuring access to affordable, reliable, sustainable and modern energy for all (Goal 7)
The spatial distribution and construction trajectory of wind turbines are prerequisites for environmental impact assessments to guide offshore wind turbine (OWT) spatial planning. This assessment directly involves the interest of developers, operators, and owners to balance income from renewable energy with ecological protection, thereby ensuring that OWTs are truly ecologically friendly and sustainable to meet the growing demand of energy
Summary
Offshore wind farms, which comprise a cluster, or array, of wind turbines, is widely accepted as renewable sources of energy and effective ways to reduce greenhouse gas emissions and promote a net-zero carbon economy. (EMODnet) wind farm database[19] and Open Power System Data (OPSD) renewable power plant database[13] (refer to details in Online-only Table 1) Among these regional/national databases, the USWTD and OPSD provide the exact OWTs location. Compared to the offshore wind farm dataset extracted or validated by aerial imagery, the wind turbine number obtained by our global OWF dataset will not be underestimated since available Sentinel 1 data do not lag actual installations by several months. This dataset can be used to analyse regional variations in OWFs, prioritize OWF planning, and assess their potential environmental impacts. The global OWF dataset will be updated annually and is currently free to download via Figshare[22]
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