GreenScapes: Optimized Vegetation Placement in Cities

Vegetation plays a central role in cities, serving functional roles such as balancing shade and sky exposure, shaping the microclimate, carbon sequestration, and providing acoustic screening. Furthermore, aesthetic choices in landscape styles (formal, modernist, picturesque) are important for citizens' well-being and should be considered in the design of urban landscapes. In this paper, we present a novel method for placing vegetation — ranging from trees to flower beds — in 3D urban scenes. Our method uses individual lots as input and employs a conditioned Vision-Language Model (VLM) to generate a top-down rendering of vegetation, including lawns, flowers, shrubs, hedges, and trees. This rendering is then converted into a 3D scene by detecting individual plants and selecting appropriate 3D assets. To obtain optimal placements for assets, we define a refinement loop that uses the VLM-generated propositions as an initial condition to perform a low-dimensional set of world-space transformations, along with discrete vegetation asset selections via CMA-ES. To define the objective function for the optimization, we evaluate the generated 3D scenes to derive the physical properties needed to simulate shade and path-based acoustic exposure indices. Furthermore, we render in-scene views in each optimization step to compute novel aesthetic metric scores, enabling the generation of aesthetic as well as functional vegetation layouts for urban scenes.