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What if the building coming down next door could become the one going up down the street?

Researchers at Cornell have created an interactive map identifying 1.8 million individual trees in New York City, with a new approach that could optimize the placement of trees for cooling in cities around the world. In the study, researchers identify the types of trees using satellite imagery as well as on-the-ground datasets and 3D data collected with lidar, short for light detection and ranging. The approach was 82% accurate overall and higher for common types of New York City trees. It’s the first “wall-to-wall,” citywide map identifying trees in natural areas and other unsurveyed areas, which together constitute an estimated 65% of the city’s canopy and have not been accounted for on previous maps. The research team will use the map to determine which trees are best for cooling, and the data could inform a host of other planting decisions where the type of tree makes a difference, from reducing allergens to managing invasive pests. Read more: news.cornell.edu/stories/202…

Satellite-derived maps of defoliation caused by European spongy moths – a devastating U.S. forest pest that consumes the leaves of a wide variety of trees – offer a promising solution for tracking where and when to spray, and for identifying large scale trends and conditions that lead to pest outbreaks, according to a new study from @CornellCALS and @CornellCAS funded in part by the @AtkinsonCenter. news.cornell.edu/stories/202…