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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:2782       Data Files Downloaded:60      
Data Downloaded:11.92 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
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