More than doubled in 2023: Mapping the photovoltaic power plants in China based on satellite data and machine learning
文献类型：期刊论文
| 作者 | Yang, Liwen1,2; Jiang, Luguang1,2; Liu, Ye2 |
| 刊名 | RENEWABLE ENERGY
 |
| 出版日期 | 2026 |
| 卷号 | 256页码:124381 |
| 关键词 | Photovoltaic Object-oriented random forest Landsat-8 Natural-social factors Annual variation China |
| ISSN号 | 0960-1481 |
| DOI | 10.1016/j.renene.2025.124381 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | China has the world's largest installed photovoltaic (PV) capacity and newly added PV capacity, making it the largest PV power generation market. To examine the layout characteristics of PV power plants and PV industry development, timely access to the latest data on PV power plants and improvements in the algorithm accuracy and operational efficiency are crucial. Based on Landsat-8 imagery, this study identifies centralized PV power plants in China for 2023 using an improved random forest algorithm on Google Earth Engine. The object-oriented random forest algorithm has better interpretation accuracy than pixel-based random forest algorithms, with Kappa value of 0.87 and overall extraction accuracy of 94 %. The area of centralized PV power plants is approximately 7458.8 km2, which is more than doubled since 2022. Xinjiang, Inner Mongolia, Hebei, Gansu, and Qinghai provinces have area exceeding 500 km2, accounting for 36.88 % of the total PV area. Grasslands comprise the largest PV area, approximately 2742.9 km2, followed by croplands and barren lands. This study optimizes existing algorithms and presents an annual update on PV data, providing a robust scientific basis for the sustainable and healthy development of the PV industry. |
| URL标识 | 查看原文 |
| WOS关键词 | SOLAR-ENERGY ; RANDOM FOREST ; LANDSAT ; WETLANDS ; SYSTEMS |
| WOS研究方向 | Science & Technology - Other Topics ; Energy & Fuels |
| 语种 | 英语 |
| WOS记录号 | WOS:001575404800003 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217551]  |
| 专题 | 资源利用与环境修复重点实验室_外文论文 |
| 通讯作者 | Jiang, Luguang |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Yang, Liwen,Jiang, Luguang,Liu, Ye. More than doubled in 2023: Mapping the photovoltaic power plants in China based on satellite data and machine learning[J]. RENEWABLE ENERGY,2026,256:124381. |
| APA | Yang, Liwen,Jiang, Luguang,&Liu, Ye.(2026).More than doubled in 2023: Mapping the photovoltaic power plants in China based on satellite data and machine learning.RENEWABLE ENERGY,256,124381. |
| MLA | Yang, Liwen,et al."More than doubled in 2023: Mapping the photovoltaic power plants in China based on satellite data and machine learning".RENEWABLE ENERGY 256(2026):124381. |
入库方式： OAI收割
来源：地理科学与资源研究所
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