METHODOLOGY-GOVERNED AI FOR REGENERATIVE URBAN PLANNING

FROM SINGLE-PASS TO ROLE-DECOMPOSED SCM EXECUTION IN DE MARKEN, ALMERE

Authors

  • Dr. Marina Matashova Co-Founder, Andorra-LAB, Professor, University of Barcelona IL-3 https://orcid.org/0009-0009-4303-1265
  • Elena Selezneva Gemeente Almere/Municipality of Almere, Urban planner

DOI:

https://doi.org/10.66838/sauc.6494

Abstract

This study tests methodology-governed LLM execution for regenerative public-realm planning in De Marken, Almere. Under a frozen municipal corpus, it compares a structured non-SCM baseline (A), single-pass Sustainable Community Masterplan (SCM) execution (B), and a staged, role-decomposed SCM workflow (C). Explicit SCM specification strengthened relational territorial reasoning and regenerative direction. Staged execution better preserved that direction through portfolio re-validation, delivery structuring and rendering. Research scores ranked C>B>A; a blind municipal evaluation ranked C>A>B. Methodological gains do not automatically become decision usefulness: overall usefulness stayed low in both single-pass conditions and rose only under staged execution. The study distinguishes specification from execution architecture and treats methodology-governed AI as municipal decision support, not autonomous planning.

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Author Biographies

Dr. Marina Matashova, Co-Founder, Andorra-LAB, Professor, University of Barcelona IL-3

Dr Marina Matashova is an architect and urban planner, and co-founder of Andorra-LAB / Forward Consulting Group. She holds a PhD in Urban Planning from the Universitat Politècnica de Catalunya (UPC–ETSAB). She is Professor of Sustainable Urbanism and Academic Coordinator for Master’s Theses at IL3–Universitat de Barcelona, and was formerly Lead Urban Planner and Project Manager at Ricardo Bofill Taller de Arquitectura. With over 20 years of international experience, her work combines territorial intelligence, sustainability strategies and performance-based accountability through the Sustainable Community Master Plan (SCM) methodology.

Elena Selezneva, Gemeente Almere/Municipality of Almere, Urban planner

Elena Selezneva is an urban planner at the Municipality of Almere, the Netherlands, with nearly a decade of experience across urban research, planning and design. She holds two master’s degrees: one in Architecture from TOGU and another in Urban Planning from Delft University of Technology. Her professional experience includes urban planning and urban design roles at the municipalities of Amsterdam, Hilversum and Almere. Previously, she worked as an urban researcher at the Urban Knowledge Platform of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdam).

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Published

2026-09-30

How to Cite

Matashova, M., & Selezneva, E. (2026). METHODOLOGY-GOVERNED AI FOR REGENERATIVE URBAN PLANNING: FROM SINGLE-PASS TO ROLE-DECOMPOSED SCM EXECUTION IN DE MARKEN, ALMERE. Street Art & Urban Creativity, 12(5), 494–515. https://doi.org/10.66838/sauc.6494

Issue

Vol. 12 No. 5 (2026)

Section

Research articles

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