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.