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Cities in transformation. Computational urban planning through big data analytics
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.
Cities in transformation. Computational urban planning through big data analytics
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.
Cities in transformation. Computational urban planning through big data analytics
Carlo Caldera (author) / Carlo Ostorero (author) / Valentino Manni (author) / Andrea Galli (author) / Luca Saverio Valzano (author)
2021
Article (Journal)
Electronic Resource
Unknown
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