\ Digital Planning through Directed Acyclic Graphs

Digital Planning through Directed Acyclic Model

Backward-Chaining Key Indicators and DPSIR Classification across Water, Heat, and Housing Systems

Department of Urban and Regional Planning and Geo-Information Management, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hallenweg 8, Enschede, 7522 NH, Overijssel, Netherlands

Iván Cardenas-Leon | Pirouz Nourian | Mila Koeva | Karin Pfeffer

DOI: in progress

Keywords: Planning Support Systems, Directed Acyclic Graph, Multi-sectoral integration, Causal reasoning, Evidence-based planning

Abstract

Digital planning for urban systems benefits from integrated frameworks that capture cross-sectoral dependencies, support causal reasoning, and adapt to diverse data sources. This paper introduces a methodological approach for Digital Twinning that combines backward-chaining analysis with directed acyclic graphs (DAGs) to identify, decompose, and interlink key performance indicators across three critical planning domains: drinking water supply, urban heat stress, and housing provision. Building on a comprehensive indicator review from prior work, we selected key targets for analysis. Using backward chaining, we trace each indicator to its fundamental components and classify variables according to the DPSIR framework (Driving Forces, Pressures, States, Impacts, and Responses). We then quantify relational dependencies and network centrality metrics to construct sector-specific DAGs, specifying required spatial data objects and metric calculation functions. Finally, we merge overlapping elements into an integrated cross-sector DAG, revealing critical causal pathways and enabling scenario testing across diverse driver variations, including climate change, demographic shifts, and credit conditions. Our results demonstrate how interventions in infrastructural and natural systems propagate through improvements in water reliability, thermal comfort, and housing affordability. The proposed framework clarifies data requirements and analytic workflows for creating effective Digital Planning tools while offering a scalable template for extending cross-sectoral impact analysis to additional urban challenges. By structuring complex interactions into a unified causal schema, this approach empowers planners to evaluate trade-offs, test policy scenarios, and support evidence-based decision-making in rapidly evolving urban contexts.

Water supply system

Causal Chain

Explore the causal chain for water supply planning and monitoring. The interactive visualization allows you to see the relationships between different indicators and their classifications.

Directed Acyclic Model

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Urban Heat Stress

Causal Chain

Explore the causal chain for urban heat stress. The interactive visualization allows you to see the relationships between different indicators and their classifications.

Directed Acyclic Model

View Heat Architecture diagram (PDF)

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Housing provision

Causal Chain

Explore the causal chain for housing provision. The interactive visualization allows you to see the relationships between different indicators and their classifications.

Directed Acyclic Model

View Housing DAG (PDF)

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Integrated Directed Acyclic Model

This is the integrated model across the three planning sectors. Explore the full model and the interrelations present from object to object. In dark blue there is a descriptive function that should be included when transforming the model into an operational tool.

View Integrated Model (PDF)

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