DeepOWT: A global offshore wind turbine data set

DeepOWT (deep learning derived global offshore wind turbines) is an independent and openly accessible data set of offshore wind energy infrastructure locations and their temporal deployment dynamics on a global scale. It is derived by applying deep learning based object detection on ESA's spaceborne Sentinel-1 synthetic aperture radar (SAR) archive. DeepOWT provides OWT locations along with their quarterly deployment stages from 2016 until 2021. It differentiates between platforms under construction, OWTs which are readily deployed and offshore wind farm substations, such as transformer stations. Related publication

File metadata

File
Time
Periods
Geometry
Entries

DeepOWT.geojson (Dataset)
2016Q3-2021Q2
20
points
9941

gt_2021Q2_nsb.geojson (Ground Truth)
2021Q2
1
polygons
4354

gt_2021Q2_ecs.geojson (Ground Truth)
2021Q2
1
polygons
2844

gt_2019Q4_nsb.geojson (Ground Truth)
2019Q4
1
polygons
3821

gt_2019Q4_ecs.geojson (Ground Truth)
2019Q4
1
polygons
1469

gt_2016Q3-2021Q1_nsb.geojson (GT)
2016Q3-2021Q1
19
polygons
650

gt_2016Q3-2021Q1_ecs.geojson (GT)
2016Q3-2021Q1
19
polygons
430

gt_nsb_gridded.geojson (GT North Sea Basin)

polygon
1

gt_ecs_gridded.geojson (GT East China Sea)

polygon
1

Mapping of integer values used in the dataset to semantic classes

Integer
Semantic label
Abbreviation

0
open sea
sea

1
under construction
const

2
offshore wind turbine
owt

3
offshore wind farm substation
sub