Urban green infrastructure provides a multitude of ecosystem services. Among others, it contributes to climate regulation through shade provisioning and transpiration. City trees are a key component in this climate regulation. A good understanding of these benefits is required to contribute to green infrastructure management and to make cities more resilient against climate change. The current knowledge on the spatially explicit quantification of cooling of urban trees, as well as differences between tree species, fails to answer related questions. The aim of this project is to contribute to a better understanding of cooling effects of urban trees. State-of-the-art techniques such as Terrestrial LiDAR Scans (TLS) will be used to identify relevant functional and structural tree characteristics that will be used to develop allometric relations. By improving an existing microscale climate model we will better assess the cooling effects of urban trees. This is achieved by modelling the effects of shading and transpiration of urban trees while taking the surrounding urban environment and their interactions into account. The ultimate goal is to create a prototype of a decision-making tool for urban tree implantation, species selection and management to maximise cooling.