Dr. Carlo Cavicchia
Period: September 2026 - August 2027
Funded by: NWO
Cities generate enormous amounts of mobility data — from public transport check-ins to bike-sharing records — offering unprecedented insight into how urban space is actually used. Yet these data remain underused in practice: origin–destination tables covering thousands of locations are typically very large and highly incomplete, with only a small fraction of possible trips ever observed.
This makes it difficult for researchers and planners to extract a clear, interpretable picture of how a city functions through movement. Traditional visualisation methods, such as classical multidimensional scaling, were not designed for data of this scale and sparsity.
In this project, I develop Sparse Multidimensional Scaling (Sparse MDS), a method that transforms large, incomplete mobility data into intuitive two-dimensional maps reflecting functional connections based on actual movement rather than geographic distance. Applied to Dutch cities, these maps can reveal high-mobility corridors, underserved areas, and transport inequalities hidden in raw data — supporting smarter transport planning, fairer access, and more sustainable urban development. The method will be released as a fully documented open-source tool.
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Selected projects from the Econometric Institute
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