FutureScapes: A design thinking approach to blending computational models and scenario narratives for urban futures

Accelerating urbanization and the inherent uncertainty in urban planning are increasing the demand for approaches that meaningfully integrate qualitative insights with quantitative analysis. While scenarios are widely used to explore multiple urban futures, existing methods that combine narrative storylines with computational models face persistent challenges: narrative assumptions are often oversimplified during translation; model structures frequently lack transparency regarding their underlying assumptions; and integrative processes tend to prioritize consensus, often sidelining the specialized insights of practitioners essential for urbanization strategies. Design Thinking (DT) offers a promising framework to address these limitations through its iterative, non-linear structure that bridges creative and analytical reasoning. Yet, a systematic, reproducible workflow that operationalizes DT for urban scenario development remains underdeveloped. This paper introduces FutureScapes (FS) , a stepwise Design Thinking methodology for blending computational models and scenario narratives that embeds expert feedback into the modelling process. FS centers the spatial reasoning of expert stakeholders and introduces semi-quantitative boundary objects—in the form of scenario design maps—to break the traditionally linear sequence from story to simulation. This enables a reflexive process where model outputs actively reshape qualitative scenario assumptions to inform policy-relevant outcomes. The study contributes a generalizable methodology that enhances the contextual relevance, transparency, and strategic utility of computational scenario modelling for metropolitan planning.

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Publication Details

Journal
Environment and Planning B Urban Analytics and City Science
Published
2026-04-24
DOI
https://doi.org/10.1177/23998083261438856
Primary Topic
Urban Planning and Governance
Type
article
Field-Weighted Citation Impact
0.00
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article

FutureScapes: A design thinking approach to blending computational models and scenario narratives for urban futures

Nazli Yonca Aydin, Hedwig van Delden, Tina Comes, Supriya Krishnan
Environment and Planning B Urban Analytics and City Science
Urban Planning and Governance
article

FutureScapes: A design thinking approach to blending computational models and scenario narratives for urban futures

Nazli Yonca Aydin, Hedwig van Delden, Tina Comes, Supriya Krishnan
article en

Abstract

Accelerating urbanization and the inherent uncertainty in urban planning are increasing the demand for approaches that meaningfully integrate qualitative insights with quantitative analysis. While scenarios are widely used to explore multiple urban futures, existing methods that combine narrative storylines with computational models face persistent challenges: narrative assumptions are often oversimplified during translation; model structures frequently lack transparency regarding their underlying assumptions; and integrative processes tend to prioritize consensus, often sidelining the specialized insights of practitioners essential for urbanization strategies. Design Thinking (DT) offers a promising framework to address these limitations through its iterative, non-linear structure that bridges creative and analytical reasoning. Yet, a systematic, reproducible workflow that operationalizes DT for urban scenario development remains underdeveloped. This paper introduces FutureScapes (FS) , a stepwise Design Thinking methodology for blending computational models and scenario narratives that embeds expert feedback into the modelling process. FS centers the spatial reasoning of expert stakeholders and introduces semi-quantitative boundary objects—in the form of scenario design maps—to break the traditionally linear sequence from story to simulation. This enables a reflexive process where model outputs actively reshape qualitative scenario assumptions to inform policy-relevant outcomes. The study contributes a generalizable methodology that enhances the contextual relevance, transparency, and strategic utility of computational scenario modelling for metropolitan planning.

Environment and Planning B Urban Analytics and City Science
Research Institute for Knowledge Systems (NL), Delft University of Technology (NL)
Sustainable cities and communities
Openalex Percentile: Top 13%
Urban Planning and Governance
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