Territorial Reasoning Beyond Coordination: Prototyping Urban Suitability Score Maps for custom readings of post-transition Tirana

In some post-transition cities characterized by dense urban palimpsest, we ob serve that urban transformation advances through a patchwork of opportunistic interventions that often contrast approved, city-wide strategies. In Tirana, the cumulative effect of such decisions is a territory where large-scale masterplans coexist with fragmentary, site-specific developments, producing both visible dy namism and deep spatial incoherence. This paper introduces a lightweight, data-driven methodology for prototyping Urban Suitability Scores (USS) as adaptable metrics which can inform and sup port decision-making. Using cadastral parcel data, a compact set of urban indicators (e.g., accessibil ity, regulatory capacity, amenity proximity), and by introducing a Lean Canvas Model as an interpretative reading bridge, we developed a generative workflow in Grasshopper (Rhinoceros 3D) that tests the possibility to translate qualitative stakeholders’ priorities into quantitative, weighted attributes. These are later clustered via a Gaussian Mixture Model (GMM) algorithm (LunchBox ML plugin) to evidence suitability classes’ fluctuation trend for targeted interventions. The clustering output renders them into spatially explicit, optimized, gradient-coded maps. This back-testing frames the tool not as a predictive engine, but as an exper imental diagnostic device for territorial reasoning. This research contributes a transferable framework for reading the fractured development trajectories of post-transitional urbanism, to reveal hidden dependencies or patterns that in form and support different urban scale related decision-making processes.