Post by TWIN2EXPAND

A recent research study from our Society and Urban Form (SURF) Research Lab Lab at the University of Cyprus, in collaboration with Chalmers University of Technology and UCL shows that automated digital tools can reliably analyse city street networks across different urban contexts, supporting faster and more cost-effective urban planning decisions. We tested automated and hybrid methods for analysing city street networks across four cities — Nicosia, London, Gothenburg, and Madrid — and the findings are promising: automated workflows can deliver comparable results for most planning needs, allowing policymakers to: ✅ Test more scenarios before committing to projects ✅ Make evidence-based decisions more quickly ✅ Allocate resources more efficiently The study “Automated versus hybrid street network modelling for centrality and accessibility analysis” published in the journal Environment and Planning B: Urban Analytics and City Science, was nominated for the journal’s best paper of the year recognition, and is available from: https://lnkd.in/dhY8FGva Walid S Abdeldayem, Ilaria Geddes, Ahmed Hazem Eldesoky, Ioanna Stavroulaki, Gareth Simons, Meta Berghauser Pont, Nadia Charalambous European Commission, Programme Horizon Europe, UKRI - Industrial Decarbonisation Challenge (IDC), UCY Faculty of Engineering | Πολυτεχνική Σχολή – Πανεπιστήμιο Κύπρου