A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on public and private lands with record-breaking speed at an unprecedented scale. The team accomplished the feat by developing a novel AI-enhanced visual computing method that accurately determines the locations of trees in over 330 U.S. cities with a population of 100,000 or more. The method so far has individually identified 280 million urban trees.

A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on public and private lands with record-breaking speed at an unprecedented scale. The team accomplished the feat by developing a novel AI-enhanced visual computing method that accurately determines the locations of trees in over 330 U.S. cities with a population of 100,000 or more. The method so far has individually identified 280 million urban trees.

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