Spatial Systems & Society

Natural disasters, poverty, food shortages, epidemics, and climate change: learn to tackle society’s complex challenges through urban design, urban planning, socio-economics insight and spatial data.

Natural disasters, poverty, food shortage, epidemics, climate change; the greatest challenges society is facing today are characterised by enormous complexity. These so-called wicked problems are impossible to solve in a way that is simple or final. The world needs socially committed engineers who won’t shy away from these complex challenges but feel the urge to contribute to solutions that will make societies around the world more sustainable and resilient. Are you eager to address these multifaceted challenges, using an in-depth understanding of spatial information science? If so, the Master’s in Spatial Engineering at the University of Twente (UT) is the right choice for you.

In this two-year, English-taught Master’s, you will learn to address large-scale and complex societal challenges by combining both technical and socio-economic knowledge with a strong basis of spatial data analysis and modelling. You will become skilled in mapping the conflicting needs of different stakeholders within complex societal, political, economic and cultural contexts. The key is to structure and redefine problems beyond the obvious frames and design solutions based on a multidisciplinary understanding of wicked problems.

In this Master’s, you will gain knowledge in three core domains:

• Spatial Information Science. When mapping out the implications of a wicked problem, whether you are talking about flooding, food shortage, deforestation or biodiversity loss, you often have to work with massive amounts of spatial data. So how do you process these datasets? And how can you visualise the problem and discover patterns? You need knowledge of Spatial Information Science to know where, when and what is happening. In this Master’s, you will become familiar with techniques for e.g. spatial data visualisation, remote sensing, image classification, spatial statistics, vegetation mapping and monitoring, 3D/temporal visualisations and crowdsourcing.
• Technical Engineering. The domain of Technical Engineering is closely linked to Spatial Information Science. Once you have collected and processed data, you need to be able to model and understand the physical (environmental) processes. For example, how can you estimate which areas are most at risk of flooding? What are the underlying principles of seismic waves, resulting from earthquakes? And how can you simulate ecological systems to monitor climate change and biodiversity loss? Within this knowledge domain, you will learn about flood modelling, systems analysis, dynamic modelling, processing UAV (Unmanned Aerial Vehicles) images, and more.
• Spatial Planning & Governance. No intervention can be successful without taking into account spatial planning and governance. For example, you need to know what stakeholders are involved and what their (conflicting) needs are, as well as the governance structures within the networks: who is in charge and who is not? And, moreover, how do you plan interventions? And does implementing an intervention in one location actually solve a problem, or will it just shift the problem to another location, harming other stakeholders? This knowledge domain covers topics such as social vulnerability, markets and value chain analysis, evidence-based policy analysis, spatial knowledge management and legal frameworks.