Ongoing projects and collaborations of the team.
Influence of Socioeconomic and Cultural Factors on Urban Structure in Central Europe
The shape of cities, formed by cultural, political, economic and technological shifts in human society, now reciprocally forms people living in them. Nonetheless, understanding patterns making up cities is limited, especially in the effects of forces shaping them into their current form. Advancements in geographic data science and the availability of urban data resulted in a growing field of urban morphometrics, a quantitative assessment of urban form, with methods that enable detailed classification of the built environment applicable beyond a metropolitan scale. This project combines advancements in morphometrics with an understanding of the socioeconomic and cultural development of Central Europe, aiming to uncover how societal shifts influenced the physical structure of towns and cities and how it affected the composition of the urban environment in individual regions. It follows the spatiotemporal development of urbanisation across five countries that show a direct contest of political and societal ideas alongside the formation and dissolution of new boundaries, unearthing the developments of urban typology from historical regional diversity to contemporary convergence.
Duration: 01/2024 – 12/2027
Principal Investigator: Martin Fleischmann
Funding: PRIMUS competition of Charles University
EuroFab: European Urban Fabric Classification Using Artificial Intelligence
The EuroFab project leverages spatial data science and modern deep learning techniques to develop a scientific, technical and applied basis for a detailed, consistent, updatable and open classification of urban fabric in Europe. The project will perform a comprehensive assessment of every building and street segment to provide a rich multiscale description of the built environment, serving as the foundation for a hierarchical classification of patterns of urban fabric, yielding easily interpretable types whose distribution will be mapped in time and space using artificial intelligence reading satellite imagery, providing valuable information for sustainable urban development, climate change mitigation, energy efficiency, renewable energy, nature-based solutions, and biodiversity conservation. The outputs produced by EuroFab contribute to define novel and more granular indicators to measure progress towards the targets set by the UN Sustainable Development Goals (SDG) framework, especially SDG11, dedicated to sustainable cities and communities, and is in line with many of the core principles behind the UN’s New Urban Agenda.
Duration: 06/2024 – 06/2025
Principal Investigator: Martin Fleischmann
Partners: The Alan Turing Institute, OECD
Funding: European Space Agency [ESA RFP/3-18468/24/I-DT-bgh]
