Fractalopolis: A multi-scale scenario-modelling approach for evaluating master plans and rebalancing metropolitan hierarchy

Metropolitan regions frequently exhibit hierarchical imbalances between central cores and peripheral subcentres, resulting in uneven accessibility, and service concentration. This paper presents Fractalopolis as a multi-scale scenario-modelling framework that encodes metropolitan hierarchy through the integration of fractal geometry, central-place logic, demographic allocation, and accessibility-based satisfaction indicators within a GIS environment. Applied to the Metropolitan City of Cagliari (Italy), a coastal-insular system characterised by strong edge effects and statutory environmental constraints, the model reproduces existing hierarchical gradients and evaluates alternative development scenarios through controlled amenity redistribution and residential additions. Results show that service-led reinforcement of peripheral nodes produces disproportionate improvements in suitability, whereas densification without proportional service upgrading yields limited gains. By embedding regulatory and ecological masking within hierarchical modelling, the study advances Fractalopolis toward a regulation-aware, transferable decision-support methodology for environmentally constrained metropolitan contexts.