光伏系统
遥感
卫星
中国
环境科学
计算机科学
深度学习
气象学
人工智能
航空航天工程
电气工程
地质学
工程类
地理
考古
作者
Yuehong Chen,Jiayue Zhou,Yong Ge,Jinwei Dong
标识
DOI:10.1016/j.rse.2024.114100
摘要
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of PV power plants available for China cannot fully address these needs due to either missing installation dates or outdated information.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 installation dates. We found that western China has a higher total PV area but a lower density of large-size PV power plants whereas eastern and central China have lower total PV areas but a higher density of small-size PV power plants. The area of PV power plants in China has over 600-fold increase from 5.86 km2 in 2010 to 3712.1 km2 in 2022 with the average annual growth of 285 km2 and western China has the highest annual growth proportion of 53%. The PV power plants in eastern and central China mainly established on croplands (24.6%) and the occupation of croplands presents a significant reduction of 48% from 2017 to 2022. In contrast, PV installations in western China, especially poverty-stricken areas, are primarily deployed on grasslands (28.3%) and unused lands (27.5%) and a declining pattern is observed in the occupation of grasslands. The up-to-date geospatial dataset of PV power plants and their expansion pattern analysis offer valuable insights into the understanding of PV development and its land occupation in both space and time, and thereby contribute to the policy-making of carbon mitigation for China.
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