Tackle large-scale, complex, societal challenges with the use of 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.
Start Master's in Spatial Engineering
The Master’s in Spatial Engineering, as well as the Pre-Master’s, starts in September. If you wish to enrol in Spatial Engineering, submit your application before the given date. Go to application deadlines.
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Making sense of our world using spatial data
Spatial data is essential when it comes to identifying, understanding and defying wicked problems, especially because of the large scale on which these problems occur. You could use remote sensing to monitor deforestation in areas such as the Amazon or melting sea ice around the North Pole. Or you could map out the impact of natural disasters such as tsunamis or earthquakes, consulting Volunteered Geographic Information (VGI). This is spatial data provided by citizens through geo-referenced data, shared via e.g. Twitter or Instagram. Within this Master’s, you will get familiar with these and many more spatial analysis and modelling techniques.
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