Generative Adversarial Network Approach to Future Sermonizing of Housing Dispersal in Emerging Cities
Publication: Journal of Urban Planning and Development
Volume 148, Issue 1
Abstract
This study aims to visualize the future housing dispersal of expatriates, based on the predicted urban growth in emerging cities. Generalized adversarial networks (GANs) will be utilized to predict the future urban growth of Doha Metropolitan emerging city. The housing dispersal of expatriates will be visualized on the predicted urban growth map to investigate housing preferences, which will be based on Gordon’s theory. This study will prove the feasibility of a process approach when practicing the management of urban growth in emerging cities worldwide. It could be a robust solution for the worsening imbalance in the urban morphology of metropolitan cities. The findings of the broad-spectrum housing dispersal guidelines could benefit the policymakers and planners for the realities of spatial patterns and future urban growth.
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Acknowledgments
This paper was made possible by NPRP grant number [NPRP 07 - 960 - 5 - 135] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.
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Published In
Journal of Urban Planning and Development
Volume 148 • Issue 1 • March 2022
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Feb 17, 2021
Accepted: Jul 30, 2021
Published online: Nov 24, 2021
Published in print: Mar 1, 2022
Discussion open until: Apr 24, 2022
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