'We Mapped Every Large Solar Plant on Earth Using Satellites and Machine Learning'
A team of researchers built a machine learning system to scan satellite images for solar energy-generating facilities greater than 10 kilowatts and then deployed the system on over 550 terabytes of imagery "using several human lifetimes of computing." Team-member Lucas Kruitwagen, a climate change/AI researcher at Oxford, reveals what they learned. "We searched almost half of Earth's land surface area, filtering out remote areas far from human populations." In total we detected 68,661 solar facilities. Using the area of these facilities, and controlling for the uncertainty in our machine learning system, we obtain a global estimate of 423 gigawatts of installed generating capacity at the end of 2018. This is very close to the International Renewable Energy Agency's (IRENA) estimate of 420 GW for the same period. Our study shows solar PV generating capacity grew by a remarkable 81% between 2016 and 2018, the period for which we had timestamped imagery. Growth was led particularly by increases in India (184%), Turkey (143%), China (120%) and Japan (119%). Facilities ranged in size from sprawling gigawatt-scale desert installations in Chile, South Africa, India and north-west China, through to commercial and industrial rooftop installations in California and Germany, rural patchwork installations in North Carolina and England, and urban patchwork installations in South Korea and Japan... Using the back catalogue of satellite imagery, we were able to estimate installation dates for 30% of the facilities. Data like this allows us to study the precise conditions which are leading to the diffusion of solar energy, and will help governments better design subsidies to encourage faster growth. Knowing where a facility is also allows us to study the unintended consequences of the growth of solar energy generation. In our study, we found that solar power plants are most often in agricultural areas, followed by grasslands and deserts. This highlights the need to carefully consider the impact that a ten-fold expansion of solar PV generating capacity will have in the coming decades on food systems, biodiversity, and lands used by vulnerable populations. Policymakers can provide incentives to instead install solar generation on rooftops which cause less land-use competition, or other renewable energy options. A note at the end of the article adds that the researchers' code and data repositories have been made available online "to facilitate more research of this type and to kickstart the creation of a complete, open, and current dataset of the planet's solar energy facilities."
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