Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/271488 
Year of Publication: 
2023
Citation: 
[Journal:] Journal of Urban Management [ISSN:] 2226-5856 [Volume:] 12 [Issue:] 1 [Year:] 2023 [Pages:] 4-15
Publisher: 
Elsevier, Amsterdam
Abstract: 
This paper aims to engage with the ongoing debates on the role of planning in future smart cities, to make a case for a reconceptualization of the technocentric notion of the smart city, and to elevate the position of city planning within the smart-city discourse. The central argument made is that the smart city could exploit the synergies between city planning and three techno-scientific domains including Big Data, Geographic Information Science and Systems, and Data Science-which collectively constitute an emerging field known as Geospatial Artificial Intelligence (GeoAI)- to meet four overarching policy goals: 1) to enhance the efficiency of urban services and functions; 2) to improve quality of life for all urban citizens; 3) to address the pressing societal, ecological and economic challenges that could plague urban systems on different levels; and, 4) to contribute to the production of spatial data, information and knowledge on human-urban dynamics. In addition, the paper defines a human-centered conceptual framework illustrating how the cross-pollination between city planning and the three techno-scientific fields could enhance the planning practice and accomplish the smart-city policy goals. The methodology employed in this study entails a systematic review of the literature. In addition to discussing the latest achievements as well as the progress made on the nexus of city planning and GeoAI, the paper also highlights the barriers to the application of GeoAI in the planning, design and management of smart cities and identifies potential avenues for future research.
Subjects: 
AI in urban planning
Geographic information science and systems
Smart city
Sustainable urban development
Urban digital twins
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size
814.97 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.