Framing Evidence-Based Design and Planning: An Analytical, Multi-Scalar and Iterative Framework for Urban Design and Planning

The increasing complexity of urban environments has exposed the limitations of prescriptive approaches in urban design and planning, highlighting the need for more adaptive, data-informed, and methodologically rigorous processes. Evidence-Based Design and Planning (EBDP) offers a promising response by embedding evidence as a continuous and iterative element throughout design and decision-making. Yet, its adoption in practice remains uneven, constrained by project limitations, data availability, and the challenge of operationalising analytical workflows. This paper addresses these challenges by proposing a transferable framework for EBDP, developed through the review of six realised projects, ranging from public space enhancements to metropolitan masterplans and policy studies, undertaken in both professional practice and academic research. Examined alongside existing theoretical models, these cases revealed recurring patterns that informed the framework. The resulting model consists of four interlinked phases: clarification and evidence-based project definition; integration of an evidence base through analysis and modelling; generation of options synthesising diverse evidence; and evaluations to guide adaptation and decision-making. Rather than a linear or prescriptive sequence of stages, the framework uses iteration and flexible feedback processes anchored by a unifying Hybrid Spatial Model to synthesise evidence, support the generation of design options, and underpin engagement and feedback processes considering project objectives. This paper offers a systematic yet flexible framework for EBDP that can be adapted across scales, project types, and contexts.