Eco-districts and data-driven smart eco-cities: Emerging approaches to strategic planning by design and spatial scaling and evaluation by technology

Abstract

In recent years, the world has witnessed significant progress in implementing numerous eco-district and eco-city projects, which are under the banner of experimentation or seen as sites of innovation. Indeed, the rise of such initiatives serves as a sign of renewed attempts to experiment or innovate in designing urban futures in an increasingly urbanized and datafied society. In light of this, a number of alternative models of eco-urbanism have been proposed by scholars and promoted by policy makers. The prominent among these models are sustainable urban districts and data-driven smart eco-cities. At the core of these models is a range of compact and ecological design strategies and static and dynamic conceptions of spatial scaling. These are intended to produce and boost the benefits of sustainability on the basis of a set of integrated approaches—increasingly supported by big data technologies—as a way to overcome new challenges and introduce new solutions. Based on two case studies conducted on three of the ecologically and technologically leading cities in Europe—Stockholm, Malmö, and Barcelona, this paper analyses and discusses the role and relevance of integrating density, mixed land use, greening, and low-energy buildings to the sustainability of emerging eco-districts; the new conceptions of cities and their spatial scales in the context of data-driven smart eco-cities; and the opportunities and challenges of smart urban metabolism with respect to the evaluation of eco-districts. This study shows that combining compact and ecological design strategies improves the performance of eco-districts with respect to the three dimensions of sustainability, as well as paves the way for their balanced integration for producing synergistic effects. Also, this study highlights the innovative potential and enabling role of urban computing and intelligence in transforming the spatial scaling of data-driven smart eco-cities through generating the kind of designs that increase the effects of sustainability as outcomes of processes. Moreover, this study reveals the advantages of the data-driven approach to the analysis of the flows of resources in urban environments in relation to the evaluation of sustainable urban district development. This paper concludes that data-driven smart planning and evaluation holds great potential for facilitating progress towards achieving the goals of sustainability thanks to the proven role and untapped potential of big data technologies in monitoring, understanding, and analyzing urban processes and systems in real-time.