We demonstrate an approach that has considerable potential for more effectively analysing urban structures. We focus upon the different neighbourhoods‟ different levels of liveability which, we argue, can be encapsulated using two types of statistic “opportunity indicators” and “success indicators”. For opportunity indicators we mapped different zones‟ “accessibility to shops” and “accessibility to jobs”, and for success indicators we mapped “average income”, “percentage of adults employed”, “tree cover” and lack of traffic. We then used what we claim to be an advance upon normal clustering methods –neural clustering, in order to cluster zones into groups that are similar. Finally, we mapped such clusters using an innovative, graphical-communication method known as face charts. By closely inspecting the maps of clustered face charts, rather than using more conventional methods, one gains more insight into the similarities and differences between our two cities.

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