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Research on Plant Allocation of Sponge City Construction Based on Deep Learning

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3D Imaging—Multidimensional Signal Processing and Deep Learning

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 348))

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Abstract

Since the construction of Sponge City in China, the research on the construction of Sponge City has mostly focused on the engineering level, and the research on the selection, function and configuration of plants has lagged behind, resulting in unreasonable plant selection, lack of “localization” of plant design, and lack of systematic and targeted consideration and design of plant landscape configuration, which has restricted the construction and development of Sponge City to some extent. Mian city can reduce urban waterlogging, improve the utilization rate of water resources, and meet the requirements of green environmental protection development in China. Through analysis, the functions of plants in Sponge City are summarized as landscaping and ecological protection. Based on the clues of meeting these two functions, combined with in-depth learning, this paper proposes the principles of plant selection and configuration under the concept of Sponge City, which provides a theoretical basis for the selection of plants in the construction of Sponge City. The paper summarizes the plants that can be used in sponge cities, and draws the common plant configuration patterns in low impact development facilities during the research process, providing relevant theoretical basis and experience for further construction of sponge cities in China.

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Correspondence to Huishan Wang .

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Wang, H., Zhao, X., Chen, J. (2023). Research on Plant Allocation of Sponge City Construction Based on Deep Learning. In: Patnaik, S., Kountchev, R., Tai, Y., Kountcheva, R. (eds) 3D Imaging—Multidimensional Signal Processing and Deep Learning. Smart Innovation, Systems and Technologies, vol 348. Springer, Singapore. https://doi.org/10.1007/978-981-99-1145-5_19

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