Computing urban futures: experimental and intelligent pipelines for adaptive and evidence-based planning

Today, urban design faces evermore complex, serious challenges and increasing uncertainty in cities, driven by planetary urbanization, socio-economic disparities, and the climate crisis. Computational approaches – AI-aided modelling, analytics, simulation – have the potential to support urban planners in managing this complexity and exploring diverse possible futures. The paper explores four thesis projects examining data-driven pipelines for planners working within unstable environmental conditions, leveraging computer vision and remote sensing to deepen our understanding of socio-spatial realities. This offers a holistic view of how computation can support planning practices by embracing a multiplicity of perspectives as a condition of contemporary urbanization.