Method to automatically estimate rooftop solar potential

Read the full story from the University of Massachusetts at Amherst.

The progress of rooftop solar installations is often slowed by a shortage of trained professionals who must use expensive tools to conduct labor-intensive structure assessments one by one, say scientists. Now researchers are proposing a new, data-driven approach that uses machine learning techniques and widely available satellite images to identify roofs that have the most potential to produce cost-effective solar power.

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