  Given the importance of urban sustainability and resilience to the future of
our planet, there is a need to better understand the interconnectedness between
the social, economic, environmental, and governance outcomes that underline
these frameworks. Here, we propose a synthesis of the independent scientific
frameworks of economic complexity and urban scaling into a consistent mechanism
- termed 'city complexity' - to measure the fitness of cities across multiple
dimensions. Essentially, we propose the use of urban scaling as the basis to
construct and populate a bipartite city-outcome matrix, whose entries are the
deviations from scaling law for a given set of urban outcomes. This matrix
forms the input into the economic complexity methodology, which iterates over a
pair of coupled non-linear maps, computing fitness of cities and complexity of
outcomes. We test our algorithm with data from American cities and find that
the emergent city fitness measure is consistent with desired behavior across
the set of outcomes studied. We also find temporal evolution of city fitness
and outcome complexity to be in agreement with theoretical expectation.
Overall, these findings suggest that the city complexity mechanism proposed
here produces a robust measure of fitness and can be applied for any set of
diverse outcomes, irrespective of the specifics of national urban contexts.
