A data-driven urban regeneration index utilising ahp and fuzzy logic for sustainable redevelopment planning

This study proposes a sustainable decision-making framework for assessing urban transformation requirements in areas vulnerable to natural disasters and urban decay. Expert opinions were evaluated using the Analytic Hierarchy Process (AHP) method based on 22 sustainability indicators grouped under five main categories. Subsequently, a fuzzy logic-based scoring system was developed to quantitatively determine the priorities for transformation. The method was applied in the city of Adana, Turkey, which has a seismically active and ageing urban fabric. Expert judgements and spatial data were integrated to create a repeatable and scalable transformation index. Unlike traditional, threshold-based policies, this approach offers a data-driven, transparent, and adaptable decision support mechanism that is compatible with local risks and sustainability goals. The model provides a practical tool for local authorities and urban planners to prioritise transformation areas based on scores. Furthermore, by bridging qualitative indicators and quantitative planning, it makes a unique contribution to the global literature on sustainable urban resilience.HighlightsA novel scoring model integrates AHP and fuzzy logic for urban transformation planning.22 sustainability indicators were identified and weighted by expert judgment.The model was applied in a high-risk urban area in Adana, Türkiye.The framework bridges expert knowledge with spatial and quantitative data.The method offers a replicable tool for sustainable urban regeneration prioritization.