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.
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
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Cited articles
Al Garni, H. Z. and Awasthi, A.:
Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia, Appl. Energ., 206, 1225–1240, https://doi.org/10.1016/j.apenergy.2017.10.024, 2017.
Aydin, N. Y., Kentel, E., and Duzgun, H. S.:
GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey, Energ. Convers. Manage., 70, 90–106, 2013.
Belgiu, M. and Drăguţ, L.:
Random forest in remote sensing: A review of applications and future directions, ISPRS J. Photogramm., 114, 24–31, https://doi.org/10.1016/j.isprsjprs.2016.01.011, 2016.
Bradbury, K., Saboo, R., L. Johnson, T., Malof, J. M., Devarajan, A., Zhang, W., M. Collins, L., and G. Newell, R.:
Distributed solar photovoltaic array location and extent dataset for remote sensing object identification, Sci. Data, 3, 160106, https://doi.org/10.1038/sdata.2016.106, 2016.
Capellán-Pérez, I., de Castro, C., and Arto, I.:
Assessing vulnerabilities and limits in the transition to renewable energies: Land requirements under 100 % solar energy scenarios, Renew. Sust. Energ. Rev., 77, 760–782, https://doi.org/10.1016/j.rser.2017.03.137, 2017.
