A Digital Twin to Improve the Sustainability of Neighbourhood Scenario Planning

Abstract. Neighbourhood sustainability planning needs tools that integrate heterogeneous urban datasets, expose modelling assumptions, and allow transparent comparison of intervention strategies across domains. Therefore, this paper presents a neighbourhood-scale urban digital twin (UDT) prototype for Twekkelerveld, Enschede, combining energy and ecological indicators in a single interactive environment. The co-developed prototype links building-level energy demand, rooftop photovoltaic potential, vegetation and tree-based ecosystem indicators, and satellite-derived urban heat information within a shared GIS-based workflow. Its main contribution is a reproducible integration pipeline that harmonises geospatial, statistical, ecological, and remote-sensing data through explicit, editable scenario-response functions. Technical validation confirmed consistent scenario behaviour. Regression-based explanatory analysis of 800 Monte Carlo runs showed that PV economic outcomes depend mainly on PV unit cost and yield assumptions, while tree annualised cost is driven by intervention cost, discounting, and time horizon. Multi-criteria decision analysis (MCDA) rankings stayed highly stable under 20% weight variation (median Spearman’s ρ ≈ 0.998), and stakeholder feedback confirmed practical usefulness for neighbourhood planning. The results show that neighbourhood-scale digital twins can support urban informatics and smart-city decision-making by making trade-offs among retrofitting, photovoltaics, greening, heat mitigation, and spatial equity visible in practice.