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المؤلفIbrahim, Hatem
المؤلفKhattab, Ziad
المؤلفKhattab, Tamer
المؤلفAbraham, Revina
تاريخ الإتاحة2022-10-31T19:21:55Z
تاريخ النشر2021
اسم المنشورHousing Policy Debate
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1080/10511482.2021.1962939
معرّف المصادر الموحدhttp://hdl.handle.net/10576/35659
الملخصHousing dispersal in emerging cities should be investigated as it occurs to achieve a better understanding of future housing dispersal. In this study, housing preferences are analyzed in Doha Metropolitan Area based on Gordon's theory. Machine learning (especially the generalized adversarial network) is utilized to predict the future urban growth of the city. The housing dispersal of expatriates is visualized in the predicted urban growth map of Doha city based on an investigation of housing supply trends, household income levels, government vision, and census data. The study proves the feasibility of this approach for managing urban growth in emerging cities worldwide. It is a robust solution to the increasing imbalance in the urban morphology of metropolitan cities. The conclusions drawn from the broad-spectrum housing dispersal findings of this study will inform policymakers and planners regarding the realities of spatial patterns and future urban growth. 2021 Informa UK Limited, trading as Taylor & Francis Group.
اللغةen
الناشرRoutledge
الموضوعgenerative adversarial network
housing dispersal
machine learning
rapidly developing metropolis
urban growth
العنوانExpatriates' Housing Dispersal Outlook in a Rapidly Developing Metropolis Based on Urban Growth Predicted Using a Machine Learning Algorithm
النوعArticle
dc.accessType Abstract Only


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