The aim of this report is to characterize European cities as a basis for the replication framework of the urban regeneration model.
This therefore represents the first step for the definition of the methodology and framework for the replication of the REMORUBAN regeneration model, from the 3 main lighthouses (Nottingham, Valladolid and Tepebasi) to the follower cities (Seraing and Miskolc), and from there, to any other city in Europe, as a holistic strategy for city transformation and planning, integrating all the existing strategies for energy, mobility, ICTs and citizen engagement.
This deliverable contributes to create a classification of the European cities based on different layers (management, financing, energy, mobility and infrastructures) and identify a replication zone where to evaluate the potential for replicating the REMOURBAN regeneration model. As a result, 41 European cities from 18 countries have been characterized and a set of groups of cities with similar profile have been established by each layer and on basis of whole criteria. Apart of the characterization of cities, it is provided the methodology applied for this purpose which covers the list of indicators, available databases enabling to classify the cities into different groups and the statistical procedure for establishing the clusters of cities.
The final goal is to define a classification of the European cities based on their main features in the application domains of the regeneration model as basis to evaluate the replication potential in the follower cities (and by extension, of the cities from the different groups), and develop the replicability plan using the regeneration model.
Therefore, this first replicability deliverable covers the starting point of the nexus between the demonstration activities in the project (direct implementation in the lighthouse cities) and the future exploitation and dissemination of the project results, being part of the strategy defined as REMOURBAN dissemination cascade, which comprises specific activities for each of these steps, leading to different levels of engagement.
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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 646511