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An Investigation on the Use of Deep Generative Model in Urban Land Use Planning
(Lodz University of Technology Press, 2023) Leung Ming Tze; Lin Minqi; Yu Peiheng
Land use planning is an important tool to ensure that the need of people can be met and the land resources can be used efficiently. It has even been suggested that land use planning is a key to sustainable development. On the other hand, there has been a recent trend to adopt the idea of deep generative models in the realm of design. Attempts have been made to investigate the feasibility to generate architectural design options by using deep generative models. It would also be of interest to extend this idea and examine how deep generative models could be adopted in urban planning tasks. In the current study, a computational workflow to adopt deep generative model for land use planning has been proposed. The land use in various tertiary planning units (TPUs) in Hong Kong was adopted as the training data. After the training process, hypothetical TPUs was fed into the model to generate options of land use planning for these planning units. Results from the current study should unfold a new dimension in the realm of land use planning, in the sense that the proposed workflow can generate options for planners for further planning development investigation.