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Data Details

Experimental Dataset for Extracting Spatial Distribution of Offshore Wind Power Generation Facilities from Sentinel 1 Radar Images


WEI Zhe1,2WANG Fangxiong*1,2HOU Yingzi1,2LI Dazhi2ZHU Jianfeng2LV Xuedong1,2ZHANG Shuai1,2GUO Zirui1,2
1 Liaoning Key Lab of Physical Geography and Geomatics，Liaoning Normal University，Dalian 116029，China2 School of Geographical Sciences，Liaoning Normal University，Dalian 116029，China

DOI:10.3974/geodb.2023.06.07.V1

Published:Jun. 2023

Visitors：867       Data Files Downloaded：54      
Data Downloaded：10.69 MB      Citations：

Key Words：

offshore wind turbines,waters off China,Sentinel 1,spatial clustering

Abstract：

By developing a SAR image stretching algorithm, the DBSCAN algorithm and spatial analysis method to extract the offshore wind power generation facilities from the Sentinel-1 radar image, taking waters off China as the experiment area, the Experimental Dataset for Extracting Spatial Distribution of Offshore Wind Power Generation Facilities from Sentinel 1 Radar Images was developed. The dataset is consisted of 6084 offshore wind power sites, and it is archived in .shp and .kmz formats, and consists of 9 data files with data size of 788 KB (Compressed into 2 files with 419 KB).

Foundation Item：

Data Citation：

WEI Zhe, WANG Fangxiong*, HOU Yingzi, LI Dazhi, ZHU Jianfeng, LV Xuedong, ZHANG Shuai, GUO Zirui.Experimental Dataset for Extracting Spatial Distribution of Offshore Wind Power Generation Facilities from Sentinel 1 Radar Images[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.06.07.V1.

References：


     [1] Dunnett, D., Wallace, J.S. Electricity generation from wave power in Canada [J]. Renewable Energy, 2009, 34(1): 179-95.
     [2] Satir, M., Murphy, F., Mcdonnell, K. Feasibility study of an offshore wind farm in the Aegean Sea, Turkey [J]. Renewable & Sustainable Energy Reviews, 2018, 81: 2552-62.
     [3] Bilgili, M., Yasar, A., Simsek, E. Offshore wind power development in Europe and its comparison with onshore counterpart [J]. Renewable & Sustainable Energy Reviews, 2011, 15(2): 905-15.
     [4] Moulas, D., Shafiee, M., Mehmanparast, A. Damage analysis of ship collisions with offshore wind turbine foundations [J]. Ocean Engineering, 2017, 143: 149-62.
     [5] Teisl, M. F., Noblet, C. L., Corey, R. R., et al. Seeing clearly in a virtual reality: Tourist reactions to an offshore wind project [J].Energy Policy, 2018, 122: 601-11.
     [6] Klain, S. C., Satterfield, T., Sinner, J., et al. Bird Killer, Industrial intruder or clean energy? Perceiving risks to ecosystem services due to an offshore wind farm [J]. Ecological Economics, 2018, 143: 111-129.
     [7] Bugnot, A. B., Mayer-pinto, M., Airoldi, L., et al. Current and projected global extent of marine built structures [J]. Nature Sustainability, 2021, 4(1): 33-41.
     [8] Central Government of the People's Republic of China. Notice of the state council on issuing an action plan for carbon peaking before 2030 [EB/OL]. (2021-10-26). [2023-5-11]. http://www.gov.cn/zhengce/content/2021-10/26/content_5644984.htm.
     [9] Global Wind Energy Council (GWEC). Global wind report 2023 [R]. https://gwec.net/globalwindreport2023/.
     [10] Zhang, T., tian, B., Sengupta, D., et al. Global offshore wind turbine dataset [J]. Scientific Data, 2021, 8: 191.
     

Data Product:

ID Data Name Data Size Operation
1 China_OWTs.kmz 275.50KB
2 China_OWTsshp.rar 144.33KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum