Research Area Spatial Information and Modelling

The research area develops and uses data-intensive and data-integrating approaches to describe, interpret and evaluate trends in settlement and open space development at different spatial levels and at high resolution. To this end, we focus on innovative research fields such as Spatial Data Science and Geospatial Artificial Intelligence (GeoAI).

In cooperation with different stakeholders, we generate socially robust knowledge and provide transformative decision support. We use co-design approaches to develop digital tools and generate alternative future scenarios of spatial developments. To this end, we provide tools and services and in particular the "Monitor of Settlement and Open Space Development (IOER Monitor)". The overarching goal is to contribute to the understanding of complex spatial relationships and dynamics through the action-oriented development and interpretation of rapidly growing and heterogeneous data sets.

Our guiding questions are:

• How can digital information bases, knowledge and tools be developed for transformative urban and regional development?
• Which spatial characteristics, patterns, cause-effect relationships and trends in settlement and open space development can be elaborated and evaluated against the background of sustainability transformation as basis for scenario-based forecasts?
• How can the research results be visualized in a comprehensible way within the framework of a research data centre? And how can the knowledge be prepared in a way that is suitable for policy-makers, society and science?

To develop answers, our mutual endeavour has led to specific approaches and themes. Among those, three thematic research groups with particular focusses have emerged:

• Urban Structure and Policy (USP) aims at fostering the integration of approaches of geoinformatics and planning science.
• Urban Complexity (UCP) investigates emergent phenomena in cities and urban systems.
• SITES.AI – the DRESDEN-concept research group on Advanced Environmental Risk and Sustainability Modelling of Cities and Regions Using AI – strives for innovations in data-intensive modelling based on artificial intelligence and data analytics.