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Wide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the influence of the emergence of these tools on the design and planning of the cities in the context of urban change. In this paper, the implications of the application of artificial-intelligence-based tools and geo-localised big data, both in solving specific research problems in the field of urban planning and design as well as on planning practice, are discussed. The paper is concluded with both cognitive conclusions and recommendations for planning practice. It is directed towards urban planners interested in the emerging urban big data analytics based on AI-related tools and towards urban theorists working on new methods of describing urban change.

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With the increasing significance of Big Data sources and their reliability for studying current urban development processes, new possibilities have appeared for analyzing the urban planning of contemporary cities. At the same time, the new urban development paradigm related to regenerative sustainability requires a new approach and hence a better understanding of the processes changing cities today, which will allow more efficient solutions to be designed and implemented. It results in the need to search for tools which will allow more advanced analyses while assessing the planning projects supporting regenerative development. Therefore, in this paper, the authors study the role of Big Data retrieved from sensor systems, social media, GPS, institutional data, or customer and transaction records. The study includes an enquiry into how Big Data relates to the ecosystem and to human activities, in supporting the development of regenerative human settlements. The aim of the study is to assess the possibilities created by Big Data-based tools in supporting regenerative design and planning and the role they can play in urban projects. In order to do this, frameworks allowing for the assessment of planning projects were analyzed according to their potential to support a regenerative approach. This has been followed by an analysis of the accessibility and reliability of the data sources. Finally, Big Data-based projects were mapped upon aspects of regenerative planning according to the introduced framework.

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