Welcome to a graduation cluster where your designs meet data and your ideas tackle real urban challenges.
In this cluster, you will learn to use spatial data, modeling, and analytics to create sustainable, climate-resilient cities—designing solutions that respond to growing pressure from urbanization, flooding, heat stress, and resource scarcity. From neighborhoods to regions, you will explore how data can guide innovative, context-sensitive spatial strategies.
You’ll dive into mapping climate vulnerability, planning adaptations across jurisdictions, and integrating environmental, infrastructural, and social data into actionable frameworks. You will work with GIS, scenario modeling, multicriteria analysis, simulations, and machine learning, turning complex datasets into clear, evidence-based design insights.
Data here is a tool, not the goal. You will translate analytics into visionary, grounded design proposals that are both practical and imaginative. Along the way, you will build technical skills, sharpen strategic thinking, and learn to communicate and collaborate effectively across disciplines—preparing you for professional work in design, planning, policy, or consultancy.
By the end of the graduation, you won’t just have designs, you’ll have tested strategies, transferable knowledge, and the confidence to contribute to sustainable, climate-ready urban futures.
Our Team
Daniele Cannatella
Data-Driven Design, Climate Adaptation
Claudiu Forgaci
Climate Adaptation
Yehan Wu
Spatial Planning
Daniela Maiullari
GIS & Modeling
Clémentine Cottineau-Mugadza
Urban Design
Anneloes Nillesen
Sustainability
Marjolein van Esch
Urban Microclimate
Camilo León-Sánchez
Urban Studies
Graduation projects highlights
Themes
Strategic Spatial Frameworks – comprehensive plans guiding urban or regional development strategies.
Integrated Climate Adaptation Plans – proposals combining design, policy, and resilience measures for climate adaptation.
Scenario-Based Design Studies – exploring alternative future scenarios to inform design decisions.
Cross-Case Comparative Analyses – comparative studies across multiple urban contexts or projects to derive transferable insights.
Data-Driven Design Prototypes – design proposals emphasizing performance metrics, simulation, and visual analytics to support decision-making.
Contact us
Daniele Cannatella d.cannatella@tudelft.nl
Claudiu Forgaci c.forgaci@tudelft.nl
For general questions about the Spatial Data and GIS Education, research opportunities, or collaboration proposals:
SDGIS Edu
sdgis@tudelft.nl
TU Delft Faculty of Architecture