In this paper we will introduce an individual-based model of a British city. The approach draws its inspiration from both microsimulation and agent-based modelling. Microsimulation is used to reconstruct the entire population of a city region at both the household and individual scale. We illustrate this for Leeds, a city with three-quarters of a million inhabitants grouped into more than 300 thousand households. The resulting population is profiled by demographic and social attributes which are richly specified. In order to incorporate dynamic individual behaviour, we argue that agent-based simulations are more appropriate, and rules will be presented which allow the identi�cation of �ve essential behaviours which we term domestic living, education, work, recreation and shopping. Through this modelling process we seek not just to understand residential patterns within the city, but the dynamic ebb and flow of the population in everyday metropolitan life. The novel feature of our research is that we will use up-to-date social network data to calibrate our agent behaviours. Although social network data are likely to be somewhat skewed and unreliable, they are abundant and continually refreshed and also provide temporally-accurate daily behavioural information that are often absent from traditional sources (such as censuses). We will make an attempt to evaluate the robustness and (potential) value of this approach.