Unprecedented Innovations in Sustainable Urban Planning: Novel Analytical Solutions and Data-Driven Decision-Making Processes

  • Simon Elias BibriEmail author
Part of the The Urban Book Series book series (UBS)


City planning is drastically changing with regard to the way urban systems can function and be managed and developed in line with the goals of sustainable development. Marking and fueling this change predominately is the increasing use and application of big data and data-driven decision-making in urban analytics and planning to advance the contribution of cities to sustainability. This unprecedented shift has been instigated by the recent advances in data science and its becoming a more accessible tool to advocacy groups, more extensive data and their new sources being able to potentially allow key stakeholders to see and respond to various urban factors (mobility, transport, energy, environment, public health care, education, etc.) in real time, coupled with citizens emitting rich spatiotemporal data to an increasing extent through the use of various technologies. We refer to big data with respect to their humongous size and wide variety but pay particular attention to urban data, i.e., data invariably tagged with spatial and temporal labels; largely streamed from diverse sensory sources and stored in databases; generated routinely, automatically, and sporadically; and merged and coalesced in data warehouses for use at the citywide scale. This epitomizes a sea change in the data that we generate about urban systems as to what happens and where, when, how, and why in the urban environment. This is opening entirely new windows of opportunity for the application of analytical solutions and data-driven decision-making approaches into urban planning in terms of improving the performance of, and contribution to, the goals of sustainable development under what is termed smart sustainable cities. This chapter explores the real potential of big data and data-driven decision-making for revolutionizing or transforming the process of planning for the purpose of achieving the goals of sustainable development in the context of smart sustainable cities, focusing on different dimensions and functions of planning as well as their synergy and integration. We argue that the increasing proliferation and availability of urban data, coupled with the continuous integration of new and more extensive sources of such data as well as the evolving development of big data technologies, are increasingly enabling novel analytical solutions for, or sophisticated engineering approaches into, advancing the process of sustainable urban development, in addition to seamlessly integrating long-term strategic planning with short-term thinking about how cities can function and be managed in the context of sustainability. In addition, we believe that big data innovations entail how new data-driven transformations are facilitated and applied as well as diffused throughout urban systems, rather than simply denoting a significant growth in volume and variety of urban data.


Smart sustainable cities Sustainable urban planning Big data analytics Data mining Data-driven decision-making Urban intelligence functions Urban simulations models Mobility data 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer and Information Science, Department of Urban Design and PlanningNorwegian University of Science and TechnologyTrondheimNorway

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