Authors
Yuehong Chen, Jiayue Zhou, Yong Ge, Jinwei Dong
Publication date
2024/5/1
Journal
Remote Sensing of Environment
Volume
305
Pages
114100
Publisher
Elsevier
Description
China's rapid deployment of solar photovoltaic (PV) power plants has positioned it as the global leader in cumulative installed capacity. The expansion patterns of PV power plants in China play a crucial role in promoting PV diffusion in markets, shaping policies, and analyzing environmental and social impacts. However, the current geospatial datasets of PV power plants available for China cannot fully address these needs due to either missing installation dates or outdated information. Hence, this study develops a framework to extract the spatial extent and installation date of PV power plants from Sentinel-2 and Landsat data using deep learning and change detection techniques and uncover their expansion patterns in China. A geospatial dataset of PV polygons with installation dates in China from 2010 to 2022 is obtained with the F1-score of 96.08% for its spatial extent and the overall accuracy of 89.86% for its …
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