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Renewable energy such as solar power is critical to fight the ever moreserious climate change. China is the world leading installer of solar panel andnumerous solar power plants were built. In this paper, we proposed a deeplearning framework named SolarNet which is designed to perform semanticsegmentation on large scale satellite imagery data to detect solar farms.SolarNet has successfully mapped 439 solar farms in China, covering near 2000square kilometers, equivalent to the size of whole Shenzhen city or two and ahalf of New York city. To the best of our knowledge, it is the first time thatwe used deep learning to reveal the locations and sizes of solar farms inChina, which could provide insights for solar power companies, market analystsand the government.

SolarNet: A Deep Learning Framework to Map Solar Power Plants In China From Satellite Imagery