Inequality within nations remains a significant challenge for socioeconomic development despite significant progress over the last 200 years (Lakner & Milanovic, 2016). Inequality harms poverty reduction (Birdsall & Londono, 1997;McKnight et al., 2017) and diminishes people's sense of fulfilment and self-worth (Friedli, 2009). It can breed crime (Kelly, 2000), mental health illnesses (Friedli, 2009), and environmental degradation (Boyce, 1994). Inequality has a strong spatial perspective (McCann, 2016) and is linked to numerous factors expanding from income to socioeconomic, health, and ethnicity (Lloyd, 2015).Geodemographic classification is a method that helps condense and understand large complex datasets (Voas & Williamson, 2001). Geodemographics cluster areal units into homogeneous groups that are similar to one another across their social, economic, and demographic conditions (Singleton & Longley, 2009). By employing geodemographic classification on spatio-temporal data, changes in socioeconomic and population structures can be studied (e.g., McLachlan & Norman, 2021). This approach effectively captures aggregate changes in local population structures. However, by comparing changes between two points in time, such an approach neglects the broader context within which these changes