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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Cited
21 citations as recorded by crossref.
- 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
- Revisiting the land use conflicts between forests and solar farms through energy efficiency P. Zhang et al. 10.1016/j.jclepro.2023.139958
- Revealing a Shift in Solar Photovoltaic Planning Sites in Vietnam from 2019 to 2022 S. Shimada & W. Takeuchi 10.3390/rs15112756
- Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine H. Zhang et al. 10.3390/rs15153712
- Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China H. Jiang et al. 10.1016/j.oceaneng.2023.115914
- Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau Y. Zeng et al. 10.1038/s41597-024-03198-z
- FEPVNet: A Network with Adaptive Strategies for Cross-Scale Mapping of Photovoltaic Panels from Multi-Source Images B. Su et al. 10.3390/rs15092469
- 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
- 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 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
- PVNet: A novel semantic segmentation model for extracting high-quality photovoltaic panels in large-scale systems from high-resolution remote sensing imagery J. Wang et al. 10.1016/j.jag.2023.103309
- 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
- Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data J. Wang et al. 10.3390/rs14246296
- 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
- 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
- Extraction of Photovoltaic Plants Using Machine Learning Methods: A Case Study of the Pilot Energy City of Golmud, China Z. Chen et al. 10.3390/rs14112697
20 citations as recorded by crossref.
- 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
- Revisiting the land use conflicts between forests and solar farms through energy efficiency P. Zhang et al. 10.1016/j.jclepro.2023.139958
- Revealing a Shift in Solar Photovoltaic Planning Sites in Vietnam from 2019 to 2022 S. Shimada & W. Takeuchi 10.3390/rs15112756
- Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine H. Zhang et al. 10.3390/rs15153712
- Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China H. Jiang et al. 10.1016/j.oceaneng.2023.115914
- Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau Y. Zeng et al. 10.1038/s41597-024-03198-z
- FEPVNet: A Network with Adaptive Strategies for Cross-Scale Mapping of Photovoltaic Panels from Multi-Source Images B. Su et al. 10.3390/rs15092469
- 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
- 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 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
- PVNet: A novel semantic segmentation model for extracting high-quality photovoltaic panels in large-scale systems from high-resolution remote sensing imagery J. Wang et al. 10.1016/j.jag.2023.103309
- 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
- Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data J. Wang et al. 10.3390/rs14246296
- 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
- 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
Latest update: 25 Apr 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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