TECHNE: Special Series Vol. 2
Essays and Viewpoint

Cities in transformation. Computational urban planning through big data analytics

Carlo Caldera
Department of Structural Engineering and Geotechnical Engineering (DISEG), Responsible Risk Resilience Centre (R3C), Politecnico di Torino, Italy
Carlo Ostorero
Department of Structural Engineering and Geotechnical (DISEG), Politecnico di Torino, Italy
Valentino Manni
Department of Architecture and Design (DAD), Politecnico di Torino, Italy
Andrea Galli
School of Architecture, Urban Planning, Construction Engineering (AUIC), Politecnico di Milano, Italy
Luca Saverio Valzano
Department of Architecture and Design (DAD), Politecnico di Torino, Italy
Published March 22, 2021
Keywords
  • City sensing,
  • Datafication,
  • Big Data analytics,
  • Computational urban planning,
  • Adaptive and inclusive urban planning
How to Cite
Caldera, C., Ostorero, C., Manni, V., Galli, A., & Valzano, L. S. (2021). Cities in transformation. Computational urban planning through big data analytics. TECHNE - Journal of Technology for Architecture and Environment, (2), 76-81. https://doi.org/10.13128/techne-10686

Abstract

Future scenarios foresee a city as a fragmented and uneven system in relation to rapidly evolving environmental, economic and social phenomena. The traditional urban planning tools, based on a theoretical-predictive approach, adapt poorly. We need to rethink how to govern the transformations of a city, which can be described by models of urban metabolism. City Sensing has changed the way a city is explored and used. With the transition from digitisation to datafication, through a computational approach, one can process georeferenced datasets within algorithms in order to achieve a higher quality of the project. This process exploits data provided by public administrations, companies and citizens taking part in inclusive and adaptive urban planning.

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