Articles | Volume 14, issue 8
https://doi.org/10.5194/essd-14-3743-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-3743-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
17 Aug 2022
Data description paper |
| 17 Aug 2022
| 17 Aug 2022
Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine
Xunhe Zhang
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China
Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China
Ming Xu
CORRESPONDING AUTHOR
BNU-HKUST Laboratory for Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, China
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
Shujian Wang
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
Yongkai Huang
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
Zunyi Xie
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China
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32 citations as recorded by crossref.
- Revisiting the land use conflicts between forests and solar farms through energy efficiency P. Zhang et al. 10.1016/j.jclepro.2023.139958
- Balancing photovoltaic development and cropland protection: Assessing agrivoltaic potential in China Z. Xia et al. 10.1016/j.spc.2024.08.001
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- Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China H. Jiang et al. 10.1016/j.oceaneng.2023.115914
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- FEPVNet: A Network with Adaptive Strategies for Cross-Scale Mapping of Photovoltaic Panels from Multi-Source Images B. Su et al. 10.3390/rs15092469
- Remote-sensing extraction and carbon emission reduction benefit assessment for centralized photovoltaic power plants in Agrivoltaic systems C. Huang et al. 10.1016/j.apenergy.2024.123585
- Water-surface photovoltaic systems have affected water physical and chemical properties and biodiversity S. Yang et al. 10.1038/s43247-024-01811-y
- Optimizing solar photovoltaic plant siting in Liangshan Prefecture, China: A policy-integrated, multi-criteria spatial planning framework L. Tang et al. 10.1016/j.solener.2024.113012
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- Characterization and mapping of photovoltaic solar power plants by Landsat imagery and random forest: A case study in Gansu Province, China X. Wang et al. 10.1016/j.jclepro.2023.138015
- Enhancing PV panel segmentation in remote sensing images with constraint refinement modules H. Tan et al. 10.1016/j.apenergy.2023.121757
- Spatial modelling the location choice of large-scale solar photovoltaic power plants: Application of interpretable machine learning techniques and the national inventory Y. Sun et al. 10.1016/j.enconman.2023.117198
- Greenness change associated with construction and operation of photovoltaic solar energy in China X. Li et al. 10.1016/j.renene.2024.120461
- Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022 M. Li et al. 10.5194/essd-15-4181-2023
- Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine H. Zhang et al. 10.3390/rs15153712
- Fast-track development of an automated solar photovoltaic module detecting framework utilizing open-access multispectral satellite imagery P. Wu et al. 10.1016/j.rsase.2024.101250
- PYS: A classification and extraction model of photovoltaics for providing more detailed data to support photovoltaic sustainable development D. Chen et al. 10.1016/j.seta.2023.103578
- Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning Y. Chen et al. 10.1016/j.rse.2024.114100
- Classification and segmentation of five photovoltaic types based on instance segmentation for generating more refined photovoltaic data D. Chen et al. 10.1016/j.apenergy.2024.124296
- Rapid mapping and spatial analysis on the distribution of photovoltaic power stations with Sentinel-1&2 images in Chinese coastal provinces W. Jiang et al. 10.1016/j.jag.2023.103280
- Mapping national-scale photovoltaic power stations using a novel enhanced photovoltaic index and evaluating carbon reduction benefits J. Wang et al. 10.1016/j.enconman.2024.118894
- Mapping global water-surface photovoltaics with satellite images Z. Xia et al. 10.1016/j.rser.2023.113760
- Fueling the future: Innovating the path to carbon-neutral skies with CO 2-to-aviation fuel G. Tian et al. 10.26599/CF.2024.9200010
- Mapping development potential and priority zones for utility-scale photovoltaic on the Qinghai-Tibet Plateau H. Yang et al. 10.1016/j.renene.2024.121546
- A high-precision oasis dataset for China from remote sensing images J. Lin et al. 10.1038/s41597-024-03553-0
- Power of SAR Imagery and Machine Learning in Monitoring Ulva prolifera: A Case Study of Sentinel-1 and Random Forest L. Zheng et al. 10.1007/s11769-024-1465-2
- Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data J. Wang et al. 10.3390/rs14246296
- Unravelling spatiotemporal patterns of solar photovoltaic plants development in China in the 21st century Z. Wang et al. 10.1088/1748-9326/ad25a3
- A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020 Q. Feng et al. 10.1038/s41597-024-02994-x
- Mapping the carbon mitigation potential of photovoltaic development in the Gobi and desert regions of China X. Lyu et al. 10.1016/j.energy.2024.132936
Latest update: 13 Dec 2024
Short summary
Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate change. A map of the PV power plants is important for policy management and environmental assessment. We established a map of PV power plants in China by 2020, covering a total area of 2917 km2. Based on the derived map, we found that most PV power plants were situated on cropland. In addition, the installation of PV power plants has generally decreased the vegetation cover.
Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate...
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