DeepOWT v2.25.1: An updated and improved global offshore wind turbine dataset until 2025Q1

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 2016Q1 until 2025Q1. It differentiates between platforms under construction, OWTs which are readily deployed and offshore wind farm substations, such as transformer stations.The dataset continues the work of 10.5194/essd-14-4251-2022. File metadata File Time Geometry Spatial extent DeepOWT.geojson (Dataset) 2016Q1-2025Q1 points Global gt_2021Q2_nsb.geojson (Ground Truth Location) 2021Q2 polygons North Sea Basin gt_2021Q2_ecs.geojson (Ground Truth Location) 2021Q2 polygons East China Sea gt_2021Q2_vtn.geojson (Ground Truth Location) 2021Q2 polygons Southeast Vietnamese Coast gt_nsb_gridded.geojson (Ground Truth Region) - polygon North Sea Basin gt_ecs_gridded.geojson (Ground Truth Region) - polygon East China Sea gt_ecs_gridded.geojson (Ground Truth Region) - polygon Southeast Vietnamese Coast Used semantic label open sea under construction offshore wind turbine offshore wind farm substation