The new generation of actors involved in spatial developments, such as architects, geo-information specialists, and decision-makers, will be expected to improve and monitor the liveability & quality of existing and new cities, landscapes, and buildings in face of new environmental, social, and economic challenges. This often requires formulating and solving multi-disciplinary complex design and decision-making problems in a collaborative setting. However, the fundamental question is: “How do we know if our interventions or designs will yield better results?” How can we model, monitor, analyse, simulate, and evaluate the functioning of cities, landscapes, and buildings? How can we improve the sustainability and liveability of cities, regions, and buildings in quantifiable ways? To effectively deal with complex multi-disciplinary problems, computational approaches need to be utilized to automate or structure analysis, synthesis & evaluation procedures required for optimization and systematic decision-making in participatory settings.
The minor Spatial Computing offers a set of courses providing the fundamentals of computing in spatial (geometrical, topological, and/or graph theoretical) monitoring, design, and spatial decision-making. The minor consists of 2 components: Geospatial Computing (Digital Twinning) & Architectural Computing (Generative Design), each of which cover the essential topics of applied mathematics and computer science topics for multi-dimensional algorithmic modelling, analysis, simulation and evaluation on building and urban scale.
The concepts, methods, and techniques learnt in the first quarter about development of larger area covering open geospatial digital twins for informing decision-making processes concerned with planning interventions will be directly utilized in the second quarter in simulation-driven architectural design of buildings.
To get an impression of some of the results achieved in the past years visit this page.
