Augmented Urban Planning

Staff Involved
M-SE Core knowledge areas
Spatial Information Science (SIS)
Spatial Planning for Governance (SPG)
Technical Engineering (TE)
Additional Remarks

Affinity with (or deep interest in) 3D modelling, geometry and topology, computer science, and mathematics (linear algebra and graph theory in particular) is expected. However, the project is not purely technical but also applied, and so, the student is expected to be familiar with or willing to research planning processes and approaches to participatory decision-making. 

Topic description

The decisions made on the spatial configurations and distributions in the built environments (urban or rural developments) directly affect the environment as well as the interests of various stakeholders. The aim of the project is to provide mechanisms for involving different stakeholders in spatial decision-making processes and facilitating their negotiations through immersion in Digital Twins equipped with simulation-based ex-ante assessment mechanisms, and Multi-Criteria Decision Analysis (MCDA) methods.

Topic objectives and methodology

The aim of the project will be to develop such a methodology and implement it as a multi-purpose Spatial Decision Support System (SDSS) or a Planning Support System (PSS) to augment the collective intelligence of the participating human actors with the objectivity and transparency of the simulation models embedded in the digital twin. The methodology is expected to be developed and formulated mathematically in the language of Linear Algebra. The implementation is expected to be carried out in Python (or R, if strongly mastered and preferred by the student). The focal point can be shifted towards the mathematical/theoretical aspects or the computational implementation and interfaces for facilitating participation. In either case, a thorough understanding of planning approaches needs to be obtained through a literature review.

Depending on the chosen challenge, various mathematical-computational formalisms and methods from graph theory, fuzzy logic, game theory, decision theory, control theory, probabilistic models, and artificial neural networks may be exploited to devise a methodology for participatory strategic planning.

References for further reading

[1] Osborne, M. J., & Rubinstein, A. (1994). A course in game theory. MIT press.

[2] Batty, M. (2013). The new science of cities. MIT press.

[3] Sugumaran, R., & Degroote, J. (2010). Spatial decision support systems: principles and practices. Crc Press.

Open Source Digital Twinning

Participatory Design in Digital Twins

How can topic be adapted to Spatial Engineering

A challenge from a particular urban context can be chosen to be worked out. The context can either be with a municipality in the Netherlands and related to the Omgevingswet, in which case the utmost utilization of open geospatial data of the Netherlands will be expected; or, a low-tech context in the global south, for which additional challenges in preparation of a minimal digital twin by using earth observation data from ESA or DLR are to be tackled.