Identifying the spatio-temporal distribution characteristics of offshore wind turbines in China from Sentinel-1 imagery using deep learning

IF 6 2区 地球科学 Q1 GEOGRAPHY, PHYSICAL GIScience & Remote Sensing Pub Date : 2024-09-25 DOI:10.1080/15481603.2024.2407389
Qiannan Ding, Bo Tian, Chunpeng Chen, Yuekai Hu, Xue Li
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Abstract

Offshore wind power is a crucial clean energy source for coastal countries and advances blue economies. Accurate spatial mapping of offshore wind turbines supports energy assessment and the sustain...
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利用深度学习从哨兵-1 图像中识别中国海上风力涡轮机的时空分布特征
近海风力发电是沿海国家的重要清洁能源,可推动蓝色经济的发展。海上风力涡轮机的精确空间测绘有助于能源评估和可持续发展。
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来源期刊
CiteScore
11.20
自引率
9.00%
发文量
84
审稿时长
6 months
期刊介绍: GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.
期刊最新文献
Synthesizing Landsat images using time series model-fitting methods for China’s coastal areas against sparse and irregular observations Methods to compare sites concerning a category’s change during various time intervals LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction Monitoring the Amazon River plume from satellite observations Identifying the spatio-temporal distribution characteristics of offshore wind turbines in China from Sentinel-1 imagery using deep learning
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