Generative Adversarial Network Approach to Future Sermonizing of Housing Dispersal in Emerging Cities

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.