Satellite imagery generates around 100 terabytes of data daily, but analyzing it proves complex. A critical question for California is quantifying fire breaks and changes since previous fire seasons. Manual analysis is limited in scalability. Neural networks have increased the efficiency of data processing by allowing algorithms to identify fire breaks in images. LGND aims to significantly reduce costs associated with data processing while enhancing human efficiency. Their product focuses on vector embeddings of geographic information, which enhances the interpretation of geographic data.
"Originally, you'd have a person look at pictures. And that only scales so far," Nathaniel Manning, co-founder and CEO of LGND, explained regarding traditional data analysis.
"We are not looking to replace people doing these things," said Bruno Sánchez-Andrade Nuño, emphasizing the goal to enhance efficiency rather than replace human effort.
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