Shaping space for ever-changing mobility. Covid-19 lesson learned from Milan and its region

In the Milan experience, Covid-19 emergency crucial issues were already hidden weaknesses of the city and its region: the limited capacity of transit transport, roads and public spaces, with crowding problems for both work and leisure. The challenge is to regenerate the competitive “human measure” o...

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Bibliographic Details
Main Authors: Diego Deponte, Giovanna Fossa, Andrea Gorrini
Format: Article
Language:English
Published: Università di Napoli Federico II 2020-06-01
Series:TeMA: Journal of Land Use, Mobility and Environment
Subjects:
Online Access:http://www.tema.unina.it/index.php/tema/article/view/6857
Description
Summary:In the Milan experience, Covid-19 emergency crucial issues were already hidden weaknesses of the city and its region: the limited capacity of transit transport, roads and public spaces, with crowding problems for both work and leisure. The challenge is to regenerate the competitive “human measure” of Milan, based on its unique relationship between public spaces and mobility, overcoming its health risk. The report raises a question on the established transit-oriented development approach, focusing on spaces “in between” and not only on nodes and networks. The traditional “invariants” welcome changes: the spatial structure of the public realm becomes a platform for ever-changing mobility and services, providing quality of life for communities, users and tourists. With this respect, streets represent by far the most strategic asset of the urban public realm. They can be reshaped in resilient infrastructure capable to respond to new forms of mobility based on a renewed Mobility-as-A-Service paradigm, as final result of different travel behaviors of the post pandemic scenario, among which an expected reduction of the overall “mobility consumption” (space) and new temporal urban rhythms (time). To this end, short-term and responsive planning becomes a crucial opportunity to enable rapidly deployed responses, through an extensive use of new analytical tools based on Open and Big data analytics and computer-based simulations.
ISSN:1970-9889
1970-9870