Thesis subject

MSc thesis topic: Understanding the Dutch urban landscape

How a city has been built has great influence on the inhabitants and visitors of that city (Venerandi et al., 2017). Additionally, there are trade-offs between urban form and social, health and sustainable wellbeing (Bielik et al., 2019 ). However, it is difficult to understand and compare the structure of cities at national and global scales.

Compared to large metropoles, Dutch cities are small, however when you compare the footprint and number of inhabitants of an urban metropolitan area, it is comparable with the Netherlands. One might say, the Netherlands is a big spread out city. In this thesis we will treat the Netherlands as a big city, studying and comparing structures outside and inside cities and their impact on the people who live there.

Early this year Wu et al (2025) proposed a language to understand the structure of cities at different inter-city scales: The Urban Pattern Language. Based on the road network and building footprints (both available as open data worldwide) they classify a city at micro, meso and macro scale in different components, revealing the patterns interlinking these scales. They apply this language to Beijing and Singapore and show that Urban Pattern Language can be used to understand a cities spatial structure.

Background

In this thesis you will use the proposed Urban Pattern Language to uncover form and function of the metropole the Netherlands using open data. Based on the pattern language we will study the Dutch urban landscape and study how we can learn from underlyitng urban structures. You will identify attractive urban structures, measured by social, health and sustainability metrics such as percentage of smokers and/or urban green. Potentially based on this work we can recommend a structures to be implemented in areas that will be developed for housing in the province of Utrecht.

Objectives and Research questions

  • Study the relationship between form and function of Dutch cities

Literature and information

Theme(s): Modelling & visualisation