Scientists Are Mapping Every Solar Panel in the World With Machine Learning

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Scientists Are Mapping Every Solar Panel in the World With Machine Learning
France Dernières Nouvelles,France Actualités
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Going over 550 terabytes of imagery and several human lifetimes worth of computing. 🧐 engineering

, and fewer penalties for over or under-generation will mean more marginal projects will be unlocked.

Using the back catalog 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.The authors compared the locations of the solar facilities to data on land use, to find out what was there before. Cropland was easily the most common.

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.

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