Current urban scale transport and land-use planning relies on input-intensive LUTI models that are inherently only capable of benchmarking predetermined infrastructure scenarios. This project attempts to further our current ability in identifying long-term land-use and transport planning targets by adapting recently developed models at the interface of complexity science and urban economics. These models, and by extension the project, bring together components from urban planning and economics together with complexity and network science modelling economic output and population-size agglomeration effects through the proxy of social interaction counts. Formulating the cities as a geographically embedded network of individual interactions dependent on the population’s skills and education levels and constrained by the mobility infrastructure network. This provides for a better understanding of the links between connectivity and productivity and for gaining insights into how infrastructure affects performance.