Re-leaf

Re-leaf uses computer vision, RGB and thermal imagery to investigate the cooling powers of trees. It investigates how different tree genera perform in different urban settings in Amsterdam, Boston, Dubai, Los Angeles, and Rome.

We compare the cooling power of each genus in different ambient temperatures, weather conditions, and urban settings. Re-leaf provides a data-informed evaluation tool to help cities to define their tree-planting schemes.

As most cities lack a comprehensive cadaster of their urban trees, we also developed an unsupervised AI framework that leverages unlabeled street-view imagery to infer the distribution of tree genera and recover key diversity indices such as Shannon and Simpson. This enables scalable monitoring of both abundance patterns and evenness across urban areas, providing cities with actionable insights to enhance the ecological and climate benefits of their green infrastructure.