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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

DeepOWT: a global offshore wind turbine data set derived with deep learning from Sentinel-1 data
Thorsten Hoeser, Stefanie Feuerstein, Claudia Kuenzer
Earth system science data (2022) Vol. 14, Iss. 9, pp. 4251-4270
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

China Building Rooftop Area: the first multi-annual (2016–2021) and high-resolution (2.5 m) building rooftop area dataset in China derived with super-resolution segmentation from Sentinel-2 imagery
Zeping Liu, Hong Tang, Lin Feng, et al.
Earth system science data (2023) Vol. 15, Iss. 8, pp. 3547-3572
Open Access | Times Cited: 31
Future global offshore wind energy under climate change and advanced wind turbine technology
Christopher Jung, Leon Sander, Dirk Schindler
Energy Conversion and Management (2024) Vol. 321, pp. 119075-119075
Open Access | Times Cited: 9
The properties of the global offshore wind turbine fleet
Christopher Jung, Dirk Schindler
Renewable and Sustainable Energy Reviews (2023) Vol. 186, pp. 113667-113667
Closed Access | Times Cited: 16
Arctic ice-wedge landscape mapping by CNN using a fusion of Radarsat constellation Mission and ArcticDEM
Michael Merchant, Laura Bourgeau‐Chavez, Masoud Mahdianpari, et al.
Remote Sensing of Environment (2024) Vol. 304, pp. 114052-114052
Closed Access | Times Cited: 5
Mapping land- and offshore-based wind turbines in China in 2023 with Sentinel-2 satellite data
Tingting He, Yihua Hu, Fashuai Li, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 214, pp. 115566-115566
Closed Access
Machine Learning Solutions for Offshore Wind Farms: A Review of Applications and Impacts
Masoud Masoumi
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 10, pp. 1855-1855
Open Access | Times Cited: 12
Improving wind and power predictions via four-dimensional data assimilation in the WRF model: case study of storms in February 2022 at Belgian offshore wind farms
Tsvetelina Ivanova, Sara Porchetta, Sophia Buckingham, et al.
Wind energy science (2025) Vol. 10, Iss. 1, pp. 245-268
Open Access
Quantification of turbid wakes in offshore wind farms using satellite remote sensing
Enora Maëlanne Lecordier, Pierre Gernez, Krysia Mazik, et al.
The Science of The Total Environment (2025) Vol. 967, pp. 178814-178814
Open Access
Semantic-to-Instance Segmentation of Time-Invariant Offshore Wind Farms Using Sentinel-1 Time Series and Time-Shift Augmentation
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Júnior, Anesmar Olino de Albuquerque, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1127-1127
Open Access
Mapping Wind Turbine Distribution in Forest Areas of China Using Deep Learning Methods
Pinpin Yang, Zhigang Zou, Wu Yang
Remote Sensing (2025) Vol. 17, Iss. 5, pp. 940-940
Open Access
From macro to micro: A multi-scale method for assessing coastal wind energy potential in China
Lirong Deng, Zhe Ding, Yang Fu
Applied Energy (2025) Vol. 389, pp. 125729-125729
Closed Access
Remote sensing unveils the explosive growth of global offshore wind turbines
Kechao Wang, Wu Xiao, Tingting He, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 191, pp. 114186-114186
Closed Access | Times Cited: 10
Deep learning-based monitoring of offshore wind turbines in Shandong Sea of China and their location analysis
Longxing Liu, Mengquan Wu, Jie Zhao, et al.
Journal of Cleaner Production (2023) Vol. 434, pp. 140415-140415
Closed Access | Times Cited: 7
Offshore wind energy potential in Shandong Sea of China revealed by ERA5 reanalysis data and remote sensing
Longxing Liu, Mengquan Wu, Yunfei Mao, et al.
Journal of Cleaner Production (2024) Vol. 464, pp. 142745-142745
Closed Access | Times Cited: 2
Automatic Geolocation and Measuring of Offshore Energy Infrastructure With Multimodal Satellite Data
Ping Ma, Malcolm Macdonald, Sally Rouse, et al.
IEEE Journal of Oceanic Engineering (2023) Vol. 49, Iss. 1, pp. 66-79
Open Access | Times Cited: 6
Identifying wind turbines from multiresolution and multibackground remote sensing imagery
Yichen Zhai, Xuehong Chen, Xin Cao, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 126, pp. 103613-103613
Open Access | Times Cited: 6
Extraction of Offshore Wind Turbines in China by Combining Multispectral and SAR Image Data
Fangxiong Wang, Shuai Zhang, Yingzi Hou, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 9266-9281
Open Access | Times Cited: 1
Marine Infrastructure Detection with Satellite Data—A Review
Robin Spanier, Claudia Kuenzer
Remote Sensing (2024) Vol. 16, Iss. 10, pp. 1675-1675
Open Access | Times Cited: 1
Lead-Time Prediction in Wind Tower Manufacturing: A Machine Learning-Based Approach
Kenny-Jesús Flores-Huamán, Alejandro Escudero-Santana, María-Luisa Muñoz-Díaz, et al.
Mathematics (2024) Vol. 12, Iss. 15, pp. 2347-2347
Open Access | Times Cited: 1
Global offshore wind turbine detection: a combined application of deep learning and Google earth engine
Shuai Zhang, Fangxiong Wang, Yingzi Hou, et al.
International Journal of Remote Sensing (2024) Vol. 45, Iss. 18, pp. 6601-6623
Closed Access | Times Cited: 1
Enhancing Wind Turbine Location Accuracy: a Deep Learning-Based Object Regression Approach for Validating Wind Turbine Geo-Coordinates
Maximilian Kleebauer, Axel Braun, D. van der Horst, et al.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (2024), pp. 7863-7867
Closed Access | Times Cited: 1
Identifying the spatio-temporal distribution characteristics of offshore wind turbines in China from Sentinel-1 imagery using deep learning
Qiannan Ding, Bo Tian, Chunpeng Chen, et al.
GIScience & Remote Sensing (2024) Vol. 61, Iss. 1
Open Access | Times Cited: 1
EXPRESS ANALYSIS OF PROBABILISTIC CHARACTERISTICS OF WIND POWER TATIONS AS A SOURCE OF ENERGY FOR SEAWATER DESALINATION IN THE AZOV-BLACK SEA REGION OF UKRAINE
П. Ф. Васько, Iryna Mazurenko
Energy Technologies & Resource Saving (2023) Vol. 77, Iss. 4, pp. 42-56
Open Access | Times Cited: 2
Satellite images reveal major discrepancies between mapped and operating wind turbines in a hotspot of wind energy development
Jacopo Cerri, Chiara Costantino, Davide De Rosa, et al.
(2024)
Open Access
TinyWT: A Large-Scale Wind Turbine Dataset of Satellite Images for Tiny Object Detection
Mingye Zhu, Zhicheng Yang, Hang Zhou, et al.
(2024), pp. 794-804
Closed Access
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