Our group focuses on the development and application of digital methods in environmental planning. We are interested in two main research questions:

1. How can environmental planners utilize large datasets, complex models, and AI-methods to support transparent and informed environmental planning and decision-making?
2. How can advanced digital methods be designed to strengthen participatory processes, ensuring that stakeholder dialogue and human negotiation remain central to complex environmental decisions?

These questions are central to the future of digital environmental planning and to addressing global challenges such as climate change and biodiversity loss.

Our primary research themes include:

• Expansion of renewable energy infrastructure
• Future land-use change
• Climate change adaptation in cities
• Biophysical climatic effects of trees and forests

Our methodological expertise and research focus include:

• Digital spatial decision support systems
• Multi-objective optimization
• Participatory and interactive optimization
• Uncertainty analysis and robust decision-making
• Statistical modeling & Machine learning
• Emulator-based environmental modeling

In our courses, students learn how to use the following digital methods in environmental planning:

• Geographic Information Systems (GIS)
• Spatial suitability analyses
• Spatial modeling based on statistical methods and machine learning
• Multi-criteria decision analysis
• Spatial optimization

   

We practice these methods and their application based on numerous examples. These include the analysis of nature-based solutions (e.g. reducing heat in cities with the help of trees), the siting of renewable energy facilities and the modeling of land use changes.