Urban greenery — like trees and other green spaces in what are otherwise concrete jungles — can help cool down cities, clean the air and encourage foot traffic, which might have the added benefit of reducing vehicle traffic. In this way, greening our cities is an important tool in our fight against climate change.
But those tasked with caring for such green spaces and planning for future ones are faced with a highly complex system whose moving parts are difficult to track and manage in full: the city itself. Now, new research from Northeastern University describes a deep learning AI model that processes both satellite imagery and Google Street View photography to analyze the green spaces in Washington, D.C., in three dimensions rather than just two. This work gives urban foresters, who plant and maintain the public green spaces in urban environments, a new planning and assessment tool that will provide them with a fresh perspective for their work.
Washington has done a good job using urban forestry and green space to create a more livable city for its residents, says Fang Fang, an associate teaching professor in Northeastern’s College of Social Sciences and Humanities. But the city, like other metropolitan cities, also faces a problem of scale, she says.
