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The 21st century will be dominated by very large urban agglomerations, qualitatively different from those big cities that our contemporary analytical understanding and models of governance are able to handle. The growth of these mega-city regions is heavily influenced by the fusion of existing cities as well as by rapid continental scale migration. This growth is generating severe problems of social segregation, connectivity, mobility, and income inequalities that require new and powerful methods of analytical understanding such as those being developed using real-time ‘big’ data sources and new information technologies.
We propose to develop a platform for prediction and urban governance using the Pearl River Delta ‘Greater Bay Area’ mega-city region as a demonstrator, bringing sustainability indicators and simulation models from the Greater London and urban Holland (the Randstad) regions to inform the development of an urban data and simulation platform relevant to designing and testing scenarios for new modes of transport and the alleviation of socio-economic inequalities in the Bay Area. These problems, we believe,
will be key mega-city regions during the rest of this century. The project will: (1) integrate already developed Land Use Transportation Interaction (LUTI) models for London and the Randstad with ongoing cellular development and transport models for the Greater Bay Area, (2) develop new indicators for measuring spatial efficiency and equity, (3) develop analytics to inform innovative policy analysis and governance, and (4) demonstrate these tools in association with planning agencies and government across the region.
Duration: Starting in 2019, ending in 2022 at the latest
Contact: Prof. Dr. Michael Batty
Partners: University College London (UCL) – Centre for Advanced Spatial Analysis (CASA), King’s College London – Geography, Vrije Universiteit Amsterdam – School of Business and Economics, Birkbeck, University of London – Geography Department, Shenzhen University – School of Architecture and Urban Planning, The University of Hong Kong – Shenzhen Institute of Research and Innovation, Sun Yat-sen University – School of Geography and Planning.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857160.