Framing Evidence-Based Design and Planning

An Analytical, Multi-Scalar and Iterative Framework for Urban Design and Planning

Dados Bibliográficos

ID13113138
AutoresKayvan Karimi (0000-0002-1461-2599, Space Syntax (United Kingdom), autor correspondente), Sepehr Zhand (0009-0003-8520-3551, Space Syntax (United Kingdom), autor correspondente), Gareth D Simons (0000-0003-3790-0638, Space Syntax (United Kingdom)), Walid Samir Abdeldayem (0000-0001-8435-8381, University of Cyprus), Nadia Charalambous (0000-0003-1977-2599, University of Cyprus), Iason Giraud (0000-0002-4414-2874, University of Cyprus)
Ano2025
Volume9
Fascículo11
Páginas457-457
Data de publicação2025-11-03
Open AccessSim
TipoARTICLE
PeriódicoUrban Science (JOURNAL)
Identificadores do periódicoISSN: 2413-8851 • E-ISSN: 2413-8851
EditoraMDPI AG (PUBLISHER • IT)
DOI10.3390/urbansci9110457
OpenAlexW4415819308
IdiomaEN
Citações recebidas2
Referências citadas44

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

Adaptation (eye · Best practice · Embedding · Framing (construction · Iterative and incremental development · Metropolitan area · Urban design · Urban planning · Urban Design and Spatial Analysis · Urban Planning and Governance · Urban Transport and Accessibility

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