Designing landscapes is a prophetic act. What will this copse look like in a decade? How might the uses and users of this space evolve? These questions are a typical part of the design process, with answers found through experience, education and precedent. However, the rapid evolution of AI-powered design tools is raising new ways to ask – and answer – questions about how landscapes perform and how landscape architects design.
Up until very recently, most AI fanfare in landscape architecture focused on enhancing our use of analysis and simulation. One example of this is at Sydney’s Bicentennial Park, where an AI model analysed soil moisture data to help direct maintenance strategies to enhance the park’s microclimates.1 Similarly, international design practice SWA has deployed AI to analyse video feeds of people interacting with public space as part of a research report that investigated the design of plazas.2
Even more speculative explorations have imagined AIs reacting to data derived from real landscapeslandscape architects and the complexities of environmental systems.3 Following this approach, an AI’s analysis of ecosystem data could highlight where to intervene during a rewilding campaign – perhaps predicting which riverbanks are most erosion-prone or where new plantings would best thrive.
