Abstract: Natural events and entities often create structure and as such exhibits scaling in their organisation in space and over time. Hierarchy is a common feature of natural and social systems. Analysis of the hierarchy could support a better understanding of the structure and the function of different places across a landscape, thus, informing better policy and interventions for sustainable development. The study examined the hierarchy in selected data at local government authorities (LGA) level. Population, road network, and boundary data were sourced, processed and analysed within ArcGIS Software to confirm agreement or otherwise with Zipf’s law and showcase the structure formed by these attributes across the LGAs in Nigeria. Head-tail break was adopted to identify the hierarchy within the datasets. Results showed that population, area, population density, and road density exhibits scaling. For population, area, population density, and road density there are 6, 5,4 and 3 classes across the LGAs. These classes represent natural and dynamic classification which are rooted in the data. Evidently, the results clearly indicate that there are more classes than the usually dichotomous classification which reinforces dualism in development. The geographic hierarchy formed by these properties gave an insight into the socio-eco-political landscape revealing the unsustainable pattern of development across the country. In conclusion, using natural classification rooted in empirical data is suggested as a better way to classify authorities thereby enhancing discussion in policy formulation to address such inequalities evident in hierarchy currently established.